Special Issue "Advanced Mobile Robotics"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (31 December 2018).

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A printed edition of this Special Issue is available here.

Special Issue Editor

Prof. Dr. DaeEun Kim
E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, Yonsei University, Shinchon, Seoul 03722, Korea
Interests: biologically inspired robotics; mobile robots; biosensors; neural networks; evolutionary computation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Mobile robotics is a challenging issue as it is a multidisciplinary field covering electrical engineering, mechanical engineering, computer science, cognitive science and social science. It is involved with the design of automated robots in mobility, in combination with artificial intelligence, vision and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications, and provide an emerging market with great potential.

To address such challenges, this Special Issue intends to handle some recent development of mobile robots and their research, and also to enhance studies on the fundamental problems observed in mobile robots. Various multidisciplinary approaches or integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are also welcome to this Special Issue from a research perspective and an application perspective.

Potential topics include, but are not limited to:

  • Motion control of mobile robots, aerial robots/vehicles, and space robots
  • Robot navigation, localization and mapping
  • Robot vision and 3D sensing
  • Active perception
  • Networked robots
  • Swarm robotics
  • Biologically-inspired robots
  • Behavior-based robotics
  • Cognitive robotics
  • Learning and adaptation in robots
  • Human–robot interaction
  • Control architecture for industrial/commercial robots

Prof. Dr. DaeEun Kim
Guest Editor

Manuscript Submission Information

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Keywords

  • mobile robots
  • navigation
  • vision
  • networked robots
  • biorobotics
  • cognitive robots

Published Papers (65 papers)

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Editorial

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Editorial
Special Feature on Advanced Mobile Robotics
Appl. Sci. 2019, 9(21), 4686; https://doi.org/10.3390/app9214686 - 04 Nov 2019
Viewed by 679
Abstract
Mobile robots and their applications are involved with many research fields including electrical engineering, mechanical engineering, computer science, artificial intelligence and cognitive science [...] Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)

Research

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Article
Robust Adaptive Path Following Control of an Unmanned Surface Vessel Subject to Input Saturation and Uncertainties
Appl. Sci. 2019, 9(9), 1815; https://doi.org/10.3390/app9091815 - 01 May 2019
Cited by 15 | Viewed by 1296
Abstract
This paper investigates the path following control problem of an unmanned surface vessel (USV) subject to input saturation and uncertainties including model parameters uncertainties and unknown time-varying external disturbances. A nonlinear robust adaptive control scheme is proposed to address the issue, more specifically, [...] Read more.
This paper investigates the path following control problem of an unmanned surface vessel (USV) subject to input saturation and uncertainties including model parameters uncertainties and unknown time-varying external disturbances. A nonlinear robust adaptive control scheme is proposed to address the issue, more specifically, steering a USV to follow the desired path at a certain velocity assignment despite the involved disturbances, by utilizing the finite-time currents observer based line-of-sight (LOS) guidance and radial basis function neural networks (RBFNN). Backstepping and Lyapunov’s direct method are the main design frameworks. Based on the finite-time currents observer and adaptive control technique, an improved LOS guidance law is proposed to obtain the desired approaching angle to the desired path, making compensations for the effects of unknown time-varying ocean currents. Then, a kinetic controller with the capability of uncertainties estimation and disturbances rejection is proposed based on the RBFNNs, where the adaptive laws including leakage terms estimate the approximation error and the unknown time-varying disturbances. Subsequently, sophisticated auxiliary control systems are employed to handle input saturation constraints of actuators. All error signals of the closed-loop system are proved to be locally uniformly ultimately bounded (UUB). Numerical simulations demonstrated the effectiveness and robustness of the proposed path following control method. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Robot Swarm Navigation and Victim Detection Using Rendezvous Consensus in Search and Rescue Operations
Appl. Sci. 2019, 9(8), 1702; https://doi.org/10.3390/app9081702 - 25 Apr 2019
Cited by 25 | Viewed by 2220
Abstract
Cooperative behaviors in multi-robot systems emerge as an excellent alternative for collaboration in search and rescue tasks to accelerate the finding survivors process and avoid risking additional lives. Although there are still several challenges to be solved, such as communication between agents, power [...] Read more.
Cooperative behaviors in multi-robot systems emerge as an excellent alternative for collaboration in search and rescue tasks to accelerate the finding survivors process and avoid risking additional lives. Although there are still several challenges to be solved, such as communication between agents, power autonomy, navigation strategies, and detection and classification of survivors, among others. The research work presented by this paper focuses on the navigation of the robot swarm and the consensus of the agents applied to the victims detection. The navigation strategy is based on the application of particle swarm theory, where the robots are the agents of the swarm. The attraction and repulsion forces that are typical in swarm particle systems are used by the multi-robot system to avoid obstacles, keep group compact and navigate to a target location. The victims are detected by each agent separately, however, once the agents agree on the existence of a possible victim, these agents separate from the general swarm by creating a sub-swarm. The sub-swarm agents use a modified rendezvous consensus algorithm to perform a formation control around the possible victims and then carry out a consensus of the information acquired by the sensors with the aim to determine the victim existence. Several experiments were conducted to test navigation, obstacle avoidance, and search for victims. Additionally, different situations were simulated with the consensus algorithm. The results show how swarm theory allows the multi-robot system navigates avoiding obstacles, finding possible victims, and settling down their possible use in search and rescue operations. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Formation Control and Distributed Goal Assignment for Multi-Agent Non-Holonomic Systems
Appl. Sci. 2019, 9(7), 1311; https://doi.org/10.3390/app9071311 - 29 Mar 2019
Cited by 7 | Viewed by 1416
Abstract
This paper presents control algorithms for multiple non-holonomic mobile robots moving in formation. Trajectory tracking based on linear feedback control is combined with inter-agent collision avoidance. Artificial potential functions (APF) are used to generate a repulsive component of the control. Stability analysis is [...] Read more.
This paper presents control algorithms for multiple non-holonomic mobile robots moving in formation. Trajectory tracking based on linear feedback control is combined with inter-agent collision avoidance. Artificial potential functions (APF) are used to generate a repulsive component of the control. Stability analysis is based on a Lyapunov-like function. Then the presented method is extended to include a goal exchange algorithm that makes the convergence of the formation much more rapid and, in addition, reduces the number of collision avoidance interactions. The extended method is theoretically justified using a Lyapunov-like function. The controller is discontinuous but the set of discontinuity points is of zero measure. The novelty of the proposed method lies in integration of the closed-loop control for non-holonomic mobile robots with the distributed goal assignment, which is usually regarded in the literature as part of trajectory planning problem. A Lyapunov-like function joins both trajectory tracking and goal assignment analyses. It is shown that distributed goal exchange supports stability of the closed-loop control system. Moreover, robots are equipped with a reactive collision avoidance mechanism, which often does not exist in the known algorithms. The effectiveness of the presented method is illustrated by numerical simulations carried out on the large formation of robots. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Effective Behavioural Dynamic Coupling through Echo State Networks
Appl. Sci. 2019, 9(7), 1300; https://doi.org/10.3390/app9071300 - 28 Mar 2019
Cited by 1 | Viewed by 841
Abstract
This work presents a novel approach and paradigm for the coupling of human and robot dynamics with respect to control. We present an adaptive system based on Reservoir Computing and Recurrent Neural Networks able to couple control signals and robotic behaviours. A supervised [...] Read more.
This work presents a novel approach and paradigm for the coupling of human and robot dynamics with respect to control. We present an adaptive system based on Reservoir Computing and Recurrent Neural Networks able to couple control signals and robotic behaviours. A supervised method is utilised for the training of the network together with an unsupervised method for the adaptation of the reservoir. The proposed method is tested and analysed using a public dataset, a set of dynamic gestures and a group of users under a scenario of robot navigation. First, the architecture is benchmarked and placed among the state of the art. Second, based on our dataset we provide an analysis for key properties of the architecture. We test and provide analysis on the variability of the lengths of the trained patterns, propagation of geometrical properties of the input signal, handling of transitions by the architecture and recognition of partial input signals. Based on the user testing scenarios, we test how the architecture responds to real scenarios and users. In conclusion, the synergistic approach that we follow shows a way forward towards human in-the-loop systems and the evidence provided establish its competitiveness with available methods, while the key properties analysed the merits of the approach to the commonly used ones. Finally, reflective remarks on the applicability and usage in other fields are discussed. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Loop Closure Detection Based on Multi-Scale Deep Feature Fusion
Appl. Sci. 2019, 9(6), 1120; https://doi.org/10.3390/app9061120 - 17 Mar 2019
Cited by 11 | Viewed by 1631
Abstract
Loop closure detection plays a very important role in the mobile robot navigation field. It is useful in achieving accurate navigation in complex environments and reducing the cumulative error of the robot’s pose estimation. The current mainstream methods are based on the visual [...] Read more.
Loop closure detection plays a very important role in the mobile robot navigation field. It is useful in achieving accurate navigation in complex environments and reducing the cumulative error of the robot’s pose estimation. The current mainstream methods are based on the visual bag of word model, but traditional image features are sensitive to illumination changes. This paper proposes a loop closure detection algorithm based on multi-scale deep feature fusion, which uses a Convolutional Neural Network (CNN) to extract more advanced and more abstract features. In order to deal with the different sizes of input images and enrich receptive fields of the feature extractor, this paper uses the spatial pyramid pooling (SPP) of multi-scale to fuse the features. In addition, considering the different contributions of each feature to loop closure detection, the paper defines the distinguishability weight of features and uses it in similarity measurement. It reduces the probability of false positives in loop closure detection. The experimental results show that the loop closure detection algorithm based on multi-scale deep feature fusion has higher precision and recall rates and is more robust to illumination changes than the mainstream methods. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Biologically-Inspired Learning and Adaptation of Self-Evolving Control for Networked Mobile Robots
Appl. Sci. 2019, 9(5), 1034; https://doi.org/10.3390/app9051034 - 12 Mar 2019
Cited by 6 | Viewed by 1261 | Correction
Abstract
This paper presents a biologically-inspired learning and adaptation method for self-evolving control of networked mobile robots. A Kalman filter (KF) algorithm is employed to develop a self-learning RBFNN (Radial Basis Function Neural Network), called the KF-RBFNN. The structure of the KF-RBFNN is optimally [...] Read more.
This paper presents a biologically-inspired learning and adaptation method for self-evolving control of networked mobile robots. A Kalman filter (KF) algorithm is employed to develop a self-learning RBFNN (Radial Basis Function Neural Network), called the KF-RBFNN. The structure of the KF-RBFNN is optimally initialized by means of a modified genetic algorithm (GA) in which a Lévy flight strategy is applied. By using the derived mathematical kinematic model of the mobile robots, the proposed GA-KF-RBFNN is utilized to design a self-evolving motion control law. The control parameters of the mobile robots are self-learned and adapted via the proposed GA-KF-RBFNN. This approach is extended to address the formation control problem of networked mobile robots by using a broadcast leader-follower control strategy. The proposed pragmatic approach circumvents the communication delay problem found in traditional networked mobile robot systems where consensus graph theory and directed topology are applied. The simulation results and numerical analysis are provided to demonstrate the merits and effectiveness of the developed GA-KF-RBFNN to achieve self-evolving formation control of networked mobile robots. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Multi-Robot Trajectory Planning and Position/Force Coordination Control in Complex Welding Tasks
Appl. Sci. 2019, 9(5), 924; https://doi.org/10.3390/app9050924 - 05 Mar 2019
Cited by 7 | Viewed by 2066
Abstract
In this paper, the trajectory planning and position/force coordination control of multi-robot systems during the welding process are discussed. Trajectory planning is the basis of the position/ force cooperative control, an object-oriented hierarchical planning control strategy is adopted firstly, which has the ability [...] Read more.
In this paper, the trajectory planning and position/force coordination control of multi-robot systems during the welding process are discussed. Trajectory planning is the basis of the position/ force cooperative control, an object-oriented hierarchical planning control strategy is adopted firstly, which has the ability to solve the problem of complex coordinate transformation, welding process requirement and constraints, etc. Furthermore, a new symmetrical internal and external adaptive variable impedance control is proposed for position/force tracking of multi-robot cooperative manipulators. Based on this control approach, the multi-robot cooperative manipulator is able to track a dynamic desired force and compensate for the unknown trajectory deviations, which result from external disturbances and calibration errors. In the end, the developed control scheme is experimentally tested on a multi-robot setup which is composed of three ESTUN industrial manipulators by welding a pipe-contact-pipe object. The simulations and experimental results are strongly proved that the proposed approach can finish the welding task smoothly and achieve a good position/force tracking performance. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Topological Map Construction Based on Region Dynamic Growing and Map Representation Method
Appl. Sci. 2019, 9(5), 816; https://doi.org/10.3390/app9050816 - 26 Feb 2019
Cited by 4 | Viewed by 1066
Abstract
In the human–machine interactive scene of the service robot, obstacle information and destination information are both required, and both kinds of information need to be saved and used at the same time. In order to solve this problem, this paper proposes a topological [...] Read more.
In the human–machine interactive scene of the service robot, obstacle information and destination information are both required, and both kinds of information need to be saved and used at the same time. In order to solve this problem, this paper proposes a topological map construction pipeline based on regional dynamic growth and a map representation method based on the conical space model. Based on the metric map, the construction pipeline can initialize the region growth point on the trajectory of the mobile robot. Next, the topological region is divided by the region dynamic growth algorithm, the map structure is simplified by the minimum spanning tree, and the similar region is merged by the region merging algorithm. After that, the parameter TM (topological information in the map) and the parameter OM (occupied information in the map) are used to represent the topological information and the occupied information. Finally, a topological map represented by the colored picture is saved by converting to color information. It is highlighted that the topological map construction pipeline is not limited by the structure of the environment, and can be automatically adjusted according to the actual environment structure. What’s more, the topological map representation method can save two kinds of map information at the same time, which simplifies the map representation structure. The experimental results show that the map construction method is flexible, and that resources such as calculation and storage are less consumed. The map representation method is convenient to use and improves the efficiency of the map in preservation. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Bio-Inspired Structure and Behavior of Self-Recovery Quadruped Robot with a Limited Number of Functional Legs
Appl. Sci. 2019, 9(4), 799; https://doi.org/10.3390/app9040799 - 25 Feb 2019
Cited by 9 | Viewed by 1841
Abstract
In this study, the authors focus on the structural design of and recovery methods for a damaged quadruped robot with a limited number of functional legs. Because the pre-designed controller cannot be executed when the robot is damaged, a control strategy to avoid [...] Read more.
In this study, the authors focus on the structural design of and recovery methods for a damaged quadruped robot with a limited number of functional legs. Because the pre-designed controller cannot be executed when the robot is damaged, a control strategy to avoid task failures in such a scenario should be developed. Not only the control method but also the shape and structure of the robot itself are significant for the robot to be able to move again after damage. We present a caterpillar-inspired quadruped robot (CIQR) and a self-learning mudskipper inspired crawling (SLMIC) algorithm in this research. The CIQR is realized by imitating the prolegs of caterpillars and by using a numerical optimization technique. A reinforcement learning method called Q-learning is employed to improve the adaptability of locomotion based on the crawling behavior of mudskipper. The results show that the proposed robotic platform and recovery method can improve the moving ability of the damaged quadruped robot with a few active legs in both simulations and experiments. Moreover, we obtained satisfactory results showing that a damaged multi-legged robot with at least one leg could travel properly along the required direction. Furthermore, the presented algorithm can successfully be employed in a damaged quadruped robot with fewer than four legs. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Numerical Evaluation of Sample Gathering Solutions for Mobile Robots
Appl. Sci. 2019, 9(4), 791; https://doi.org/10.3390/app9040791 - 23 Feb 2019
Cited by 3 | Viewed by 1285
Abstract
This paper applies mathematical modeling and solution numerical evaluation to the problem of collecting a set of samples scattered throughout a graph environment and transporting them to a storage facility. A team of identical robots is available, where each robot has a limited [...] Read more.
This paper applies mathematical modeling and solution numerical evaluation to the problem of collecting a set of samples scattered throughout a graph environment and transporting them to a storage facility. A team of identical robots is available, where each robot has a limited amount of energy and it can carry one sample at a time. The graph weights are related to energy and time consumed for moving between adjacent nodes, and thus, the task is transformed to a specific optimal assignment problem. The design of the mathematical model starts from a mixed-integer linear programming problem whose solution yields an optimal movement plan that minimizes the total time for gathering all samples. For reducing the computational complexity of the optimal solution, we develop two sub-optimal relaxations and then we quantitatively compare all the approaches based on extensive numerical simulations. The numerical evaluation yields a decision diagram that can help a user to choose the appropriate method for a given problem instance. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Cooperative Path Planning for Multiple Mobile Robots via HAFSA and an Expansion Logic Strategy
Appl. Sci. 2019, 9(4), 672; https://doi.org/10.3390/app9040672 - 16 Feb 2019
Cited by 8 | Viewed by 1128
Abstract
The cooperative path planning problem of multiple mobile robots in an unknown indoor environment is considered in this article. We presented a novel obstacle avoidance and real-time navigation algorithm. The proposed approach consisted of global path planning and local path planning via HAFSA [...] Read more.
The cooperative path planning problem of multiple mobile robots in an unknown indoor environment is considered in this article. We presented a novel obstacle avoidance and real-time navigation algorithm. The proposed approach consisted of global path planning and local path planning via HAFSA (hybrid artificial fish swarm algorithm) and an expansion logic strategy. Meanwhile, a kind of scoring function was developed, which shortened the time of local path planning and improved the decision-making ability of the path planning algorithm. Finally, using STDR (simple two dimensional robot simulator) and RVIZ (robot operating system visualizer), a multiple mobile robot simulation platform was designed to verify the presented real-time navigation algorithm. Simulation experiments were performed to validate the effectiveness of the proposed path planning method for multiple mobile robots. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Automated Enemy Avoidance of Unmanned Aerial Vehicles Based on Reinforcement Learning
Appl. Sci. 2019, 9(4), 669; https://doi.org/10.3390/app9040669 - 15 Feb 2019
Cited by 9 | Viewed by 1305
Abstract
This paper focuses on one of the collision avoidance scenarios for unmanned aerial vehicles (UAVs), where the UAV needs to avoid collision with the enemy UAV during its flying path to the goal point. Such a type of problem is defined as the [...] Read more.
This paper focuses on one of the collision avoidance scenarios for unmanned aerial vehicles (UAVs), where the UAV needs to avoid collision with the enemy UAV during its flying path to the goal point. Such a type of problem is defined as the enemy avoidance problem in this paper. To deal with this problem, a learning based framework is proposed. Under this framework, the enemy avoidance problem is formulated as a Markov Decision Process (MDP), and the maneuver policies for the UAV are learned based on a temporal-difference reinforcement learning method called Sarsa. To handle the enemy avoidance problem in continuous state space, the Cerebellar Model Arithmetic Computer (CMAC) function approximation technique is embodied in the proposed framework. Furthermore, a hardware-in-the-loop (HITL) simulation environment is established. Simulation results show that the UAV agent can learn a satisfying policy under the proposed framework. Comparing with the random policy and the fixed-rule policy, the learned policy can achieve a far higher possibility in reaching the goal point without colliding with the enemy UAV. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Iterative Learning Method for In-Flight Auto-Tuning of UAV Controllers Based on Basic Sensory Information
Appl. Sci. 2019, 9(4), 648; https://doi.org/10.3390/app9040648 - 14 Feb 2019
Cited by 10 | Viewed by 1462
Abstract
With an increasing number of multirotor unmanned aerial vehicles (UAVs), solutions supporting the improvement in their precision of operation and safety of autonomous flights are gaining importance. They are particularly crucial in transportation tasks, where control systems are required to provide a stable [...] Read more.
With an increasing number of multirotor unmanned aerial vehicles (UAVs), solutions supporting the improvement in their precision of operation and safety of autonomous flights are gaining importance. They are particularly crucial in transportation tasks, where control systems are required to provide a stable and controllable flight in various environmental conditions, especially after changing the total mass of the UAV (by adding extra load). In the paper, the problem of using only available basic sensory information for fast, locally best, iterative real-time auto-tuning of parameters of fixed-gain altitude controllers is considered. The machine learning method proposed for this purpose is based on a modified zero-order optimization algorithm (golden-search algorithm) and bootstrapping technique. It has been validated in numerous simulations and real-world experiments in terms of its effectiveness in such aspects as: the impact of environmental disturbances (wind gusts); flight with change in mass; and change of sensory information sources in the auto-tuning procedure. The main advantage of the proposed method is that for the trajectory primitives repeatedly followed by an UAV (for programmed controller gains), the method effectively minimizes the selected performance index (cost function). Such a performance index might, e.g., express indirect requirements about tracking quality and energy expenditure. In the paper, a comprehensive description of the method, as well as a wide discussion of the results obtained from experiments conducted in the AeroLab for a low-cost UAV (Bebop 2), are included. The results have confirmed high efficiency of the method at the expected, low computational complexity. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Expanded Douglas–Peucker Polygonal Approximation and Opposite Angle-Based Exact Cell Decomposition for Path Planning with Curvilinear Obstacles
Appl. Sci. 2019, 9(4), 638; https://doi.org/10.3390/app9040638 - 14 Feb 2019
Cited by 12 | Viewed by 1479
Abstract
The Expanded Douglas–Peucker (EDP) polygonal approximation algorithm and its application method for the Opposite Angle-Based Exact Cell Decomposition (OAECD) are proposed for the mobile robot path-planning problem with curvilinear obstacles. The performance of the proposed algorithm is compared with the existing Douglas–Peucker (DP) [...] Read more.
The Expanded Douglas–Peucker (EDP) polygonal approximation algorithm and its application method for the Opposite Angle-Based Exact Cell Decomposition (OAECD) are proposed for the mobile robot path-planning problem with curvilinear obstacles. The performance of the proposed algorithm is compared with the existing Douglas–Peucker (DP) polygonal approximation and vertical cell decomposition algorithm. The experimental results show that the path generated by the OAECD algorithm with EDP approximation appears much more natural and efficient than the path generated by the vertical cell decomposition algorithm with DP approximation. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Solving the Time-Varying Inverse Kinematics Problem for the Da Vinci Surgical Robot
Appl. Sci. 2019, 9(3), 546; https://doi.org/10.3390/app9030546 - 06 Feb 2019
Cited by 7 | Viewed by 2243
Abstract
A dialytic-elimination and Newton-iteration based quasi-analytic inverse kinematics approach is proposed for the 6 degree of freedom (DOF) active slave manipulator in the Da Vinci surgical robot and other similar systems. First, the transformation matrix-based inverse kinematics model is derived; then, its high-dimensional [...] Read more.
A dialytic-elimination and Newton-iteration based quasi-analytic inverse kinematics approach is proposed for the 6 degree of freedom (DOF) active slave manipulator in the Da Vinci surgical robot and other similar systems. First, the transformation matrix-based inverse kinematics model is derived; then, its high-dimensional nonlinear equations are transformed to a high-order nonlinear equation with only one unknown variable by using the dialytic elimination with a unitary matrix. Finally, the quasi-analytic solution is eventually obtained by the Newton iteration method. Simulations are conducted, and the result show that the proposed quasi-analytic approach has advantages in terms of accuracy (error < 0.00004 degree (or mm)), solution speed (<20 ms) and is barely affected by the singularity during intermediate calculations, which proves that the approach meets the real-time and high-accuracy requirements of master–slave mapping control for the Da Vinci surgical robots and other similar systems. In addition, the proposed approach can also serve as a design reference for other types of robotic arms that do not satisfy the Pieper principle. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Learning an Efficient Gait Cycle of a Biped Robot Based on Reinforcement Learning and Artificial Neural Networks
Appl. Sci. 2019, 9(3), 502; https://doi.org/10.3390/app9030502 - 01 Feb 2019
Cited by 14 | Viewed by 2020
Abstract
Programming robots for performing different activities requires calculating sequences of values of their joints by taking into account many factors, such as stability and efficiency, at the same time. Particularly for walking, state of the art techniques to approximate these sequences are based [...] Read more.
Programming robots for performing different activities requires calculating sequences of values of their joints by taking into account many factors, such as stability and efficiency, at the same time. Particularly for walking, state of the art techniques to approximate these sequences are based on reinforcement learning (RL). In this work we propose a multi-level system, where the same RL method is used first to learn the configuration of robot joints (poses) that allow it to stand with stability, and then in the second level, we find the sequence of poses that let it reach the furthest distance in the shortest time, while avoiding falling down and keeping a straight path. In order to evaluate this, we focus on measuring the time it takes for the robot to travel a certain distance. To our knowledge, this is the first work focusing both on speed and precision of the trajectory at the same time. We implement our model in a simulated environment using q-learning. We compare with the built-in walking modes of an NAO robot by improving normal-speed and enhancing robustness in fast-speed. The proposed model can be extended to other tasks and is independent of a particular robot model. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Navigating a Service Robot for Indoor Complex Environments
Appl. Sci. 2019, 9(3), 491; https://doi.org/10.3390/app9030491 - 31 Jan 2019
Cited by 3 | Viewed by 1276
Abstract
This paper investigates the use of an autonomous service robot in an indoor complex environment, such as a hospital ward or a retirement home. This type of service robot not only needs to plan and find paths around obstacles, but must also interact [...] Read more.
This paper investigates the use of an autonomous service robot in an indoor complex environment, such as a hospital ward or a retirement home. This type of service robot not only needs to plan and find paths around obstacles, but must also interact with caregivers or patients. This study presents a type of service robot that combines the image from a 3D depth camera with infrared sensors, and the inputs from multiple sonar sensors in an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based approach in path planning. In personal contacts, facial features are used to perform person recognition in order to discriminate between staff, patients, or a stranger. In the case of staff, the service robot can perform a follow-me function if requested. The robot can also use an additional feature which is to classify the person’s gender. The purpose of facial and gender recognition includes helping to present choices for suitable destinations to the user. Experiments were done in cramped but open spaces, as well as confined passages scenarios, and in almost all cases, the autonomous robots were able to reach their destinations. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Modal Planning for Cooperative Non-Prehensile Manipulation by Mobile Robots
Appl. Sci. 2019, 9(3), 462; https://doi.org/10.3390/app9030462 - 29 Jan 2019
Cited by 3 | Viewed by 1480
Abstract
If we define a mode as a set of specific configurations that hold the same constraint, and if we investigate their transitions beforehand, we can efficiently probe the configuration space by using a manipulation planner. However, when multiple mobile robots together manipulate an [...] Read more.
If we define a mode as a set of specific configurations that hold the same constraint, and if we investigate their transitions beforehand, we can efficiently probe the configuration space by using a manipulation planner. However, when multiple mobile robots together manipulate an object by using the non-prehensile method, the candidates for the modes and their transitions become enormous because of the numerous contacts among the object, the environment, and the robots. In some cases, the constraints on the object, which include a combination of robot contacts and environmental contacts, are incapable of guaranteeing the object’s stability. Furthermore, some transitions cannot appear because of geometrical and functional restrictions of the robots. Therefore, in this paper, we propose a method to narrow down the possible modes and transitions between modes by excluding the impossible modes and transitions from the viewpoint of statics, kinematics, and geometry. We first generated modes that described an object’s contact set from the robots and the environment while ignoring their exact configurations. Each multi-contact set exerted by the robots and the environment satisfied the condition necessary for the force closure on the object along with gravity. Second, we listed every possible transition between the modes by determining whether or not the given robot could actively change the contacts with geometrical feasibility. Finally, we performed two simulations to validate our method on specific manipulation tasks. Our method can be used in various cases of non-prehensile manipulations by using mobile robots. The mode transition graph generated by our method was used to efficiently sequence the manipulation actions before deciding the detailed configuration planning. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Serpens: A Highly Compliant Low-Cost ROS-Based Snake Robot with Series Elastic Actuators, Stereoscopic Vision and a Screw-Less Assembly Mechanism
Appl. Sci. 2019, 9(3), 396; https://doi.org/10.3390/app9030396 - 24 Jan 2019
Cited by 9 | Viewed by 2669
Abstract
Snake robot locomotion in a cluttered environment where the snake robot utilises a sensory-perceptual system to perceive the surrounding operational environment for means of propulsion is defined as perception-driven obstacle-aided locomotion (POAL). From a control point of view, achieving POAL with traditional rigidly-actuated [...] Read more.
Snake robot locomotion in a cluttered environment where the snake robot utilises a sensory-perceptual system to perceive the surrounding operational environment for means of propulsion is defined as perception-driven obstacle-aided locomotion (POAL). From a control point of view, achieving POAL with traditional rigidly-actuated robots is challenging because of the complex interaction between the snake robot and the immediate environment. To simplify the control complexity, compliant motion and fine torque control on each joint is essential. Accordingly, intrinsically elastic joints have become progressively prominent over the last years for a variety robotic applications. Commonly, elastic joints are considered to outperform rigid actuation in terms of peak dynamics, robustness, and energy efficiency. Even though a few examples of elastic snake robots exist, they are generally expensive to manufacture and tailored to custom-made hardware/software components that are not openly available off-the-shelf. In this work, Serpens, a newly-designed low-cost, open-source and highly-compliant multi-purpose modular snake robot with series elastic actuator (SEA) is presented. Serpens features precision torque control and stereoscopic vision. Only low-cost commercial-off-the-shelf (COTS) components are adopted. The robot modules can be 3D-printed by using Fused Deposition Modelling (FDM) manufacturing technology, thus making the rapid-prototyping process very economical and fast. A screw-less assembly mechanism allows for connecting the modules and reconfigure the robot in a very reliable and robust manner. The concept of modularity is also applied to the system architecture on both the software and hardware sides. Each module is independent, being controlled by a self-reliant controller board. The software architecture is based on the Robot Operating System (ROS). This paper describes the design of Serpens and presents preliminary simulation and experimental results, which illustrate its performance. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
A Master-Slave Separate Parallel Intelligent Mobile Robot Used for Autonomous Pallet Transportation
Appl. Sci. 2019, 9(3), 368; https://doi.org/10.3390/app9030368 - 22 Jan 2019
Cited by 6 | Viewed by 2673
Abstract
This work reports a master-slave separate parallel intelligent mobile robot for the fully autonomous transportation of pallets in the smart factory logistics. This separate parallel intelligent mobile robot consists of two independent sub robots, one master robot and one slave robot. It is [...] Read more.
This work reports a master-slave separate parallel intelligent mobile robot for the fully autonomous transportation of pallets in the smart factory logistics. This separate parallel intelligent mobile robot consists of two independent sub robots, one master robot and one slave robot. It is similar to two forks of the forklift, but the slave robot does not have any physical or mechanical connection with the master robot. A compact driving unit was designed and used to ensure access to the narrow free entry under the pallets. It was also possible for the mobile robot to perform a synchronous pallet lifting action. In order to ensure the consistency and synchronization of the motions of the two sub robots, high-gain observer was used to synchronize the moving speed, the lifting speed and the relative position. Compared with the traditional forklift AGV (Automated Guided Vehicle), the mobile robot has the advantages of more compact structure, higher expandability and safety. It can move flexibly and take zero-radius turn. Therefore, the intelligent mobile robot is quite suitable for the standardized logistics factory with small working space. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Pick and Place Operations in Logistics Using a Mobile Manipulator Controlled with Deep Reinforcement Learning
Appl. Sci. 2019, 9(2), 348; https://doi.org/10.3390/app9020348 - 21 Jan 2019
Cited by 13 | Viewed by 4666
Abstract
Programming robots to perform complex tasks is a very expensive job. Traditional path planning and control are able to generate point to point collision free trajectories, but when the tasks to be performed are complex, traditional planning and control become complex tasks. This [...] Read more.
Programming robots to perform complex tasks is a very expensive job. Traditional path planning and control are able to generate point to point collision free trajectories, but when the tasks to be performed are complex, traditional planning and control become complex tasks. This study focused on robotic operations in logistics, specifically, on picking objects in unstructured areas using a mobile manipulator configuration. The mobile manipulator has to be able to place its base in a correct place so the arm is able to plan a trajectory up to an object in a table. A deep reinforcement learning (DRL) approach was selected to solve this type of complex control tasks. Using the arm planner’s feedback, a controller for the robot base is learned, which guides the platform to such a place where the arm is able to plan a trajectory up to the object. In addition the performance of two DRL algorithms ((Deep Deterministic Policy Gradient (DDPG)) and (Proximal Policy Optimisation (PPO)) is compared within the context of a concrete robotic task. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Combining Subgoal Graphs with Reinforcement Learning to Build a Rational Pathfinder
Appl. Sci. 2019, 9(2), 323; https://doi.org/10.3390/app9020323 - 17 Jan 2019
Cited by 4 | Viewed by 1038
Abstract
In this paper, we present a hierarchical path planning framework called SG–RL (subgoal graphs–reinforcement learning), to plan rational paths for agents maneuvering in continuous and uncertain environments. By “rational”, we mean (1) efficient path planning to eliminate first-move lags; (2) collision-free and smooth [...] Read more.
In this paper, we present a hierarchical path planning framework called SG–RL (subgoal graphs–reinforcement learning), to plan rational paths for agents maneuvering in continuous and uncertain environments. By “rational”, we mean (1) efficient path planning to eliminate first-move lags; (2) collision-free and smooth for agents with kinematic constraints satisfied. SG–RL works in a two-level manner. At the first level, SG–RL uses a geometric path-planning method, i.e., simple subgoal graphs (SSGs), to efficiently find optimal abstract paths, also called subgoal sequences. At the second level, SG–RL uses an RL method, i.e., least-squares policy iteration (LSPI), to learn near-optimal motion-planning policies which can generate kinematically feasible and collision-free trajectories between adjacent subgoals. The first advantage of the proposed method is that SSG can solve the limitations of sparse reward and local minima trap for RL agents; thus, LSPI can be used to generate paths in complex environments. The second advantage is that, when the environment changes slightly (i.e., unexpected obstacles appearing), SG–RL does not need to reconstruct subgoal graphs and replan subgoal sequences using SSGs, since LSPI can deal with uncertainties by exploiting its generalization ability to handle changes in environments. Simulation experiments in representative scenarios demonstrate that, compared with existing methods, SG–RL can work well on large-scale maps with relatively low action-switching frequencies and shorter path lengths, and SG–RL can deal with small changes in environments. We further demonstrate that the design of reward functions and the types of training environments are important factors for learning feasible policies. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Comparison of Spray Deposition, Control Efficacy on Wheat Aphids and Working Efficiency in the Wheat Field of the Unmanned Aerial Vehicle with Boom Sprayer and Two Conventional Knapsack Sprayers
Appl. Sci. 2019, 9(2), 218; https://doi.org/10.3390/app9020218 - 09 Jan 2019
Cited by 29 | Viewed by 2460
Abstract
As a new low volume application technology, unmanned aerial vehicle (UAV) application is developing quickly in China. The aim of this study was to compare the droplet deposition, control efficacy and working efficiency of a six-rotor UAV with a self-propelled boom sprayer and [...] Read more.
As a new low volume application technology, unmanned aerial vehicle (UAV) application is developing quickly in China. The aim of this study was to compare the droplet deposition, control efficacy and working efficiency of a six-rotor UAV with a self-propelled boom sprayer and two conventional knapsack sprayers on the wheat crop. The total deposition of UAV and other sprayers were not statistically significant, but significantly lower for run-off. The deposition uniformity and droplets penetrability of the UAV were poor. The deposition variation coefficient of the UAV was 87.2%, which was higher than the boom sprayer of 31.2%. The deposition on the third top leaf was only 50.0% compared to the boom sprayer. The area of coverage of the UAV was 2.2% under the spray volume of 10 L/ha. The control efficacy on wheat aphids of UAV was 70.9%, which was comparable to other sprayers. The working efficiency of UAV was 4.11 ha/h, which was roughly 1.7–20.0 times higher than the three other sprayers. Comparable control efficacy results suggest that UAV application could be a viable strategy to control pests with higher efficiency. Further improvement on deposition uniformity and penetrability are needed. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Power Assist Control Based on Human Motion Estimation Using Motion Sensors for Powered Exoskeleton without Binding Legs
Appl. Sci. 2019, 9(1), 164; https://doi.org/10.3390/app9010164 - 04 Jan 2019
Cited by 1 | Viewed by 1871
Abstract
In this study, we propose a novel power assist control method for a powered exoskeleton without binding its legs. The proposed method uses motion sensors on the wearer’s torso and legs to estimate his/her motion to enable the powered exoskeleton to assist with [...] Read more.
In this study, we propose a novel power assist control method for a powered exoskeleton without binding its legs. The proposed method uses motion sensors on the wearer’s torso and legs to estimate his/her motion to enable the powered exoskeleton to assist with the estimated motion. It can detect the start of walking motion quickly because it does not prevent the motion of the wearer’s knees at the beginning of the walk. A nine-axis motion sensor on the wearer’s body is designed to work robustly in very hot and humid spaces, where an electromyograph is not reliable due to the wearer’s sweat. Moreover, the sensor avoids repeated impact during the walk because it is attached to the body of the wearer. Our powered exoskeleton recognizes the motion of the wearer based on a database and accordingly predicts the motion of the powered exoskeleton that supports the wearer. Experiments were conducted to prove the validity of the proposed method. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Algorithm for Base Action Set Generation Focusing on Undiscovered Sensor Values
Appl. Sci. 2019, 9(1), 161; https://doi.org/10.3390/app9010161 - 04 Jan 2019
Cited by 2 | Viewed by 992
Abstract
Previous machine learning algorithms use a given base action set designed by hand or enable locomotion for a complicated task through trial and error processes with a sophisticated reward function. These generated actions are designed for a specific task, which makes it difficult [...] Read more.
Previous machine learning algorithms use a given base action set designed by hand or enable locomotion for a complicated task through trial and error processes with a sophisticated reward function. These generated actions are designed for a specific task, which makes it difficult to apply them to other tasks. This paper proposes an algorithm to obtain a base action set that does not depend on specific tasks and that is usable universally. The proposed algorithm enables as much interoperability among multiple tasks and machine learning methods as possible. A base action set that effectively changes the external environment was chosen as a candidate. The algorithm obtains this base action set on the basis of the hypothesis that an action to effectively change the external environment can be found by observing events to find undiscovered sensor values. The process of obtaining a base action set was validated through a simulation experiment with a differential wheeled robot. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Tarantula: Design, Modeling, and Kinematic Identification of a Quadruped Wheeled Robot
Appl. Sci. 2019, 9(1), 94; https://doi.org/10.3390/app9010094 - 27 Dec 2018
Cited by 15 | Viewed by 2276
Abstract
This paper firstly presents the design and modeling of a quadruped wheeled robot named Tarantula. It has four legs each having four degrees of freedom with a proximal end attached to the trunk and the wheels for locomotion connected at the distal [...] Read more.
This paper firstly presents the design and modeling of a quadruped wheeled robot named Tarantula. It has four legs each having four degrees of freedom with a proximal end attached to the trunk and the wheels for locomotion connected at the distal end. The two legs in the front and two at the back are actuated using two motors which are placed inside the trunk for simultaneous abduction or adduction. It is designed to manually reconfigure its topology as per the cross-sections of the drainage system. The bi-directional suspension system is designed using a single damper to prevent the trunk and inside components from shock. Formulation for kinematics of the wheels that is coupled with the kinematics of each leg is presented. We proposed the cost-effective method which is also an on-site approach to estimate the kinematic parameters and the effective trunk dimension after assembly of the quadruped robot using the monocular camera and ArUco markers instead of high-end devices like a laser tracker or coordinate measurement machine. The measurement technique is evaluated experimentally and the same set up was used for trajectory tracking of the Tarantula. The experimental method for the kinematic identification presented here can be easily extended to the other mobile robots with serial architecture designed legs. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Multi-Criteria Decision Making for Efficient Tiling Path Planning in a Tetris-Inspired Self-Reconfigurable Cleaning Robot
Appl. Sci. 2019, 9(1), 63; https://doi.org/10.3390/app9010063 - 25 Dec 2018
Cited by 6 | Viewed by 1326
Abstract
In this study, we aim to optimize and improve the efficiency of a Tetris-inspired reconfigurable cleaning robot. Multi-criteria decision making (MCDM) is utilized as a powerful tool to target this aim by introducing the best solution among others in terms of lower energy [...] Read more.
In this study, we aim to optimize and improve the efficiency of a Tetris-inspired reconfigurable cleaning robot. Multi-criteria decision making (MCDM) is utilized as a powerful tool to target this aim by introducing the best solution among others in terms of lower energy consumption and greater area coverage. Regarding the Tetris-inspired structure, polyomino tiling theory is utilized to generate tiling path-planning maps which are evaluated via MCDM to seek a solution that can deliver the best balance between the two mentioned key issues; energy and area coverage. In order to obtain a tiling area that better meets the requirements of polyomino tiling theorems, first, the whole area is decomposed into five smaller sub-areas based on furniture layout. Afterward, four tetromino tiling theorems are applied to each sub-area to give the tiling sets that govern the robot navigation strategy in terms of shape-shifting tiles. Then, the area coverage and energy consumption are calculated and eventually, these key values are considered as the decision criteria in a MCDM process to select the best tiling set in each sub-area, and following the aggregation of best tiling path-plannings, the robot navigation is oriented towards efficiency and improved optimality. Also, for each sub-area, a preference order for the tiling sets is put forward. Based on simulation results, the tiling theorem that can best serve all sub-areas turns out to be the same. Moreover, a comparison between a fixed-morphology mechanism with the current approach further advocates the proposed technique. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Design and Experimental Evaluation of a Single-Actuator Continuous Hopping Robot Using the Geared Symmetric Multi-Bar Mechanism
Appl. Sci. 2019, 9(1), 13; https://doi.org/10.3390/app9010013 - 20 Dec 2018
Cited by 12 | Viewed by 3550
Abstract
This paper proposes the design and performance evaluation of a miniaturized continuous hopping robot RHop for unstructured terrain. The hopping mechanism of RHop is realized by an optimized geared symmetric closed-chain multi-bar mechanism that is transformed from the eight-bar mechanism, and the actuator [...] Read more.
This paper proposes the design and performance evaluation of a miniaturized continuous hopping robot RHop for unstructured terrain. The hopping mechanism of RHop is realized by an optimized geared symmetric closed-chain multi-bar mechanism that is transformed from the eight-bar mechanism, and the actuator of RHop is realized by a servo motor and the clockwork spring, thereby enabling RHop to realize continuous hopping while its motor rotates continuously only in one direction. Comparative simulations and experiments are conducted for RHop. The results show that RHop can realize better continuous hopping performance, as well as the improvement of energy conversion efficiency from 70.98% to 76.29% when the clockwork spring is applied in the actuator. In addition, comparisons with some state-of-the-art hopping robots are conducted, and the normalized results show that RHop has a better energy storage speed. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Predictable Trajectory Planning of Industrial Robots with Constraints
Appl. Sci. 2018, 8(12), 2648; https://doi.org/10.3390/app8122648 - 17 Dec 2018
Cited by 3 | Viewed by 1016
Abstract
Trajectory prediction is currently attracting considerable attention. This paper proposes geodesic trajectory planning with end-effector and joint constraints to predict the trajectory properties of the end-effector, such as velocities, accelerations, and smoothness. The prediction of the trajectory properties is independent of the joint [...] Read more.
Trajectory prediction is currently attracting considerable attention. This paper proposes geodesic trajectory planning with end-effector and joint constraints to predict the trajectory properties of the end-effector, such as velocities, accelerations, and smoothness. The prediction of the trajectory properties is independent of the joint trajectories. The prediction makes it possible to adjust the trajectory properties in line with a light computational burden. To demonstrate the effectiveness of the proposed method, experiments were conducted using the Efort robot. The experiments show that the proposed method can predict the properties of the trajectory and modify the trajectory to meet the constraints. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Alpine Skiing Robot Using a Passive Turn with Variable Mechanism
Appl. Sci. 2018, 8(12), 2643; https://doi.org/10.3390/app8122643 - 17 Dec 2018
Cited by 2 | Viewed by 1502
Abstract
Recently, the number of alpine ski junior players in Japan has drastically decreased. The causes include a decrease in ski areas and instructors, along with difficulty of early childhood alpine ski guidance. The alpine ski competition is not simply a glide on a [...] Read more.
Recently, the number of alpine ski junior players in Japan has drastically decreased. The causes include a decrease in ski areas and instructors, along with difficulty of early childhood alpine ski guidance. The alpine ski competition is not simply a glide on a slope. It requires understanding of ski deflection and skier posture mechanics. Therefore, a passive ski robot without an actuator was developed for junior racers of the alpine ski competition to facilitate understanding of the turn mechanism. Using this robot can elucidate factors affecting ski turns, such as the position of the center of gravity (COG) and the ski shape. Furthermore, a mechanism for changing the COG height, the edge angle and the ski deflection is added to the passive turn type ski robot. The developed ski robot can freely control the turn by changing those parameters during sliding. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
The Effects on Muscle Activity and Discomfort of Varying Load Carriage With and Without an Augmentation Exoskeleton
Appl. Sci. 2018, 8(12), 2638; https://doi.org/10.3390/app8122638 - 16 Dec 2018
Cited by 6 | Viewed by 1245
Abstract
Load carriage is a key risk factor for Muscular Skeletal Disorders (MSDs). As one way to decrease such injuries, some exoskeletons have been developed for regular load carriage. We examined the ergonomic potential of an augmentation exoskeleton. Nine subjects completed eight trials of [...] Read more.
Load carriage is a key risk factor for Muscular Skeletal Disorders (MSDs). As one way to decrease such injuries, some exoskeletons have been developed for regular load carriage. We examined the ergonomic potential of an augmentation exoskeleton. Nine subjects completed eight trials of carrying tasks, using four loading levels (0, 15, 30, and 45 kg) and two carrying conditions (with and without the exoskeleton). Electromyography (EMG) and the extended NASA-TLX rating scales were investigated and analyzed by linear mixed modeling and two-way ANOVA methods. Noraxon MR3.8, SPSS19.0, and MATLAB R2014b software were adapted. The results show that most of the muscle mean activities increased significantly (p < 0.05) with exoskeleton assistance. However, the interactive effects illustrate a decreasing trend with increase of load level. The mean discomfort rating scale values were generally higher, but subjects generally preferred using the exoskeleton in heavier loading tasks. The exoskeleton can effectively augment the performance of humans in heavy load carriage. The main reasons for higher muscle activity are from inflexible structures and inharmonious human–robot interactions. In order to decrease the MSD risks and increase comfort, optimal human–robot control strategies and adaptable kinematic design should be improved. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
An Adaptive Neural Non-Singular Fast-Terminal Sliding-Mode Control for Industrial Robotic Manipulators
Appl. Sci. 2018, 8(12), 2562; https://doi.org/10.3390/app8122562 - 10 Dec 2018
Cited by 31 | Viewed by 2011
Abstract
In this study, a robust control strategy is suggested for industrial robotic manipulators. First, to minimize the effects of disturbances and dynamic uncertainties, while achieving faster response times and removing the singularity problem, a nonsingular fast terminal sliding function is proposed. Second, to [...] Read more.
In this study, a robust control strategy is suggested for industrial robotic manipulators. First, to minimize the effects of disturbances and dynamic uncertainties, while achieving faster response times and removing the singularity problem, a nonsingular fast terminal sliding function is proposed. Second, to achieve the proposed tracking trajectory and chattering phenomenon elimination, a robust control strategy is designed for the robotic manipulator based on the proposed sliding function and a continuous adaptive control law. Furthermore, the dynamical model of the robotic system is estimated by applying a radial basis function neural network. Thanks to those techniques, the proposed system can operate free of an exact robotic model. The suggested system provides high tracking accuracy, robustness, and fast response with minimal positional errors compared to other control strategies. Proof of the robustness and stability of the suggested system has been verified by the Lyapunov theory. In simulation analyses, the simulated results present the effectiveness of the suggested strategy for the joint position tracking control of a 3-degree of freedom (3-DOF) PUMA560 robot. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
IMU-Assisted 2D SLAM Method for Low-Texture and Dynamic Environments
Appl. Sci. 2018, 8(12), 2534; https://doi.org/10.3390/app8122534 - 07 Dec 2018
Cited by 11 | Viewed by 1947
Abstract
Generally, the key issues of 2D LiDAR-based simultaneous localization and mapping (SLAM) for indoor application include data association (DA) and closed-loop detection. Particularly, a low-texture environment, which refers to no obvious changes between two consecutive scanning outputs, with moving objects existing in the [...] Read more.
Generally, the key issues of 2D LiDAR-based simultaneous localization and mapping (SLAM) for indoor application include data association (DA) and closed-loop detection. Particularly, a low-texture environment, which refers to no obvious changes between two consecutive scanning outputs, with moving objects existing in the environment will bring great challenges on DA and the closed-loop detection, and the accuracy and consistency of SLAM may be badly affected. There is not much literature that addresses this issue. In this paper, a mapping strategy is firstly exploited to improve the performance of the 2D SLAM in dynamic environments. Secondly, a fusion method which combines the IMU sensor with a 2D LiDAR, based on framework of extended Kalman Filter (EKF), is proposed to enhance the performance under low-texture environments. In the front-end of the proposed SLAM method, initial motion estimation is obtained from the output of EKF, and it can be taken as the initial pose for the scan matching problem. Then the scan matching problem can be optimized by the Levenberg–Marquardt (LM) algorithm. For the back-end optimization, a sparse pose adjustment (SPA) method is employed. To improve the accuracy, the grid map is updated with the bicubic interpolation method for derivative computing. With the improvements both in the DA process and the back-end optimization stage, the accuracy and consistency of SLAM results in low-texture environments is enhanced. Qualitative and quantitative experiments with open-loop and closed-loop cases have been conducted and the results are analyzed, confirming that the proposed method is effective in low-texture and dynamic indoor environments. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Optimal Collision-Free Grip Planning for Biped Climbing Robots in Complex Truss Environment
Appl. Sci. 2018, 8(12), 2533; https://doi.org/10.3390/app8122533 - 07 Dec 2018
Cited by 5 | Viewed by 1217
Abstract
Biped climbing robots (BiCRs) can overcome obstacles and perform transition easily thanks to their superior flexibility. However, to move in a complex truss environment, grips from the original point to the destination, as a sequence of anchor points along the route, are indispensable. [...] Read more.
Biped climbing robots (BiCRs) can overcome obstacles and perform transition easily thanks to their superior flexibility. However, to move in a complex truss environment, grips from the original point to the destination, as a sequence of anchor points along the route, are indispensable. In this paper, a grip planning method is presented for BiCRs generating optimal collision-free grip sequences, as a continuation of our previous work on global path planning. A mathematic model is firstly built up for computing the operational regions for negotiating obstacle members. Then a grip optimization model is proposed to determine the grips within each operational region for transition or for obstacle negotiation. This model ensures the total number of required climbing steps is minimized and the transition grips are with good manipulability. Lastly, the entire grip sequence satisfying the robot kinematic constraint is generated by a gait interpreter. Simulations are conducted with our self-developed biped climbing robot (Climbot), to verify the effectiveness and efficiency of the proposed methodology. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Design and Experiment of a Variable Spray System for Unmanned Aerial Vehicles Based on PID and PWM Control
Appl. Sci. 2018, 8(12), 2482; https://doi.org/10.3390/app8122482 - 03 Dec 2018
Cited by 18 | Viewed by 2433
Abstract
Unmanned aerial vehicle (UAV) variable-rate spraying technology, as the development direction of aviation for plant protection in the future, has been developed rapidly in recent years. In the actual agricultural production, the severity of plant diseases and insect pests varies in different locations. [...] Read more.
Unmanned aerial vehicle (UAV) variable-rate spraying technology, as the development direction of aviation for plant protection in the future, has been developed rapidly in recent years. In the actual agricultural production, the severity of plant diseases and insect pests varies in different locations. In order to reduce the waste of pesticides, pesticides should be applied according to the severity of pests, insects and weeds. On the basis of explaining the plant diseases and insect pests map in the target area, a pulse width modulation variable spray system is designed. Moreover, the STMicroelectronics-32 (STM32) chip is invoked as the core of the control system. The system combines with sensor technology to get the prescription value through real-time interpretation of prescription diagram in operation. Then, a pulse square wave with variable duty cycles is generated to adjust the flow rate. A closed-loop Proportional-Integral-Derivative (PID) control algorithm is used to shorten the time of system reaching steady state. The results indicate that the deviation between volume and target traffic is stable, which is within 2.16%. When the duty cycle of the square wave is within the range of 40% to 100%, the flow range of the single nozzle varies from 0.16 L/min to 0.54 L/min. Variable spray operation under different spray requirements is achieved. The outdoor tests of variable spray system show that the variable spray system can adjust the flow rapidly according to the prescription value set in the prescription map. The proportion of actual droplet deposition and deposition density in the operation unit is consistent with the prescription value, which proves the effectiveness of the designed variable spray system. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Disturbance-Rejection Control for the Hover and Transition Modes of a Negative-Buoyancy Quad Tilt-Rotor Autonomous Underwater Vehicle
Appl. Sci. 2018, 8(12), 2459; https://doi.org/10.3390/app8122459 - 02 Dec 2018
Cited by 7 | Viewed by 1377
Abstract
This paper proposes a Negative-buoyancy Quad Tilt-rotor Autonomous Underwater Vehicle (NQTAUV), for which an attitude-tracking controller is designed for the hover and transition modes based on a disturbance-rejection control scheme. First, the structure of NQTAUV is illustrated, a mathematical model based on the [...] Read more.
This paper proposes a Negative-buoyancy Quad Tilt-rotor Autonomous Underwater Vehicle (NQTAUV), for which an attitude-tracking controller is designed for the hover and transition modes based on a disturbance-rejection control scheme. First, the structure of NQTAUV is illustrated, a mathematical model based on the Rodrigues parameters is proposed, and the attitude-tracking error model is derived. To simplify the disturbance-observer design procedure, a disturbance observer with a single parameter was designed to estimate the disturbance torque acting on the vehicle. The controller was designed to track the target attitude, and the stability of the whole system is analyzed. Finally, the performance of the proposed method was validated by three experiments. The primary benefit of the proposed method is the simplicity of its tuning and implementation. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
MIM_SLAM: A Multi-Level ICP Matching Method for Mobile Robot in Large-Scale and Sparse Scenes
Appl. Sci. 2018, 8(12), 2432; https://doi.org/10.3390/app8122432 - 30 Nov 2018
Cited by 11 | Viewed by 1096
Abstract
In large-scale and sparse scenes, such as farmland, orchards, mines, and substations, 3D simultaneous localization and mapping are challenging matters that need to address issues such as maintaining reliable data association for scarce environmental information and reducing the computational complexity of global optimization [...] Read more.
In large-scale and sparse scenes, such as farmland, orchards, mines, and substations, 3D simultaneous localization and mapping are challenging matters that need to address issues such as maintaining reliable data association for scarce environmental information and reducing the computational complexity of global optimization for large-scale scenes. To solve these problems, a real-time incremental simultaneous localization and mapping algorithm called MIM_SLAM is proposed in this paper. This algorithm is applied in mobile robots to build a map on a non-flat road with a 3D LiDAR sensor. MIM_SLAM’s main contribution is that multi-level ICP (Iterative Closest Point) matching is used to solve the data association problem, a Fisher information matrix is used to describe the uncertainty of the estimated pose, and these poses are optimized by the incremental optimization method, which can greatly reduce the computational cost. Then, a map with a high consistency will be established. The proposed algorithm has been evaluated in the real indoor and outdoor scenes as well as two substations and benchmarking dataset from KITTI with the characteristics of sparse and large-scale. Results show that the proposed algorithm has a high mapping accuracy and meets the real-time requirements. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Design and Experiment of a Novel Façade Cleaning Robot with a Biped Mechanism
Appl. Sci. 2018, 8(12), 2398; https://doi.org/10.3390/app8122398 - 26 Nov 2018
Cited by 8 | Viewed by 1624
Abstract
Façade cleaning in high-rise buildings has always been considered a hazardous task when carried out by labor forces. Even though numerous studies have focused on the development of glass façade cleaning systems, the available technologies in this domain are limited and their performances [...] Read more.
Façade cleaning in high-rise buildings has always been considered a hazardous task when carried out by labor forces. Even though numerous studies have focused on the development of glass façade cleaning systems, the available technologies in this domain are limited and their performances are broadly affected by the frames that connect the glass panels. These frames generally act as a barrier for the glass façade cleaning robots to cross over from one glass panel to another, which leads to a performance degradation in terms of area coverage. We present a new class of façade cleaning robot with a biped mechanism that is able overcome these obstacles to maximize its area coverage. The developed robot uses active suction cups to adhere to glass walls and adopts mechanical linkage to navigate the glass surface to perform cleaning. This research addresses the design challenges in realizing the developed robot. Its control system consists of inverse kinematics, a fifth polynomial interpolation, and sequential control. Experiments were conducted in a real scenario, and the results indicate that the developed robot achieves significantly higher coverage performance by overcoming both negative and positive obstacles in a glass panel. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Stability Criterion for Dynamic Gaits of Quadruped Robot
Appl. Sci. 2018, 8(12), 2381; https://doi.org/10.3390/app8122381 - 25 Nov 2018
Cited by 8 | Viewed by 1697
Abstract
Dynamic-stability criteria are crucial for robot’s motion planning and balance recovery. Nevertheless, few studies focus on the motion stability of quadruped robots with dynamic gait, none of which have accurately evaluated the robots’ stability. To fill the gaps in this field, this paper [...] Read more.
Dynamic-stability criteria are crucial for robot’s motion planning and balance recovery. Nevertheless, few studies focus on the motion stability of quadruped robots with dynamic gait, none of which have accurately evaluated the robots’ stability. To fill the gaps in this field, this paper presents a new stability criterion for the motion of quadruped robots with dynamic gaits running over irregular terrain. The traditional zero-moment point (ZMP) is improved to analyze the motion on irregular terrain precisely for dynamic gaits. A dynamic-stability criterion and measurement are proposed to determine the stability state of the robot and to evaluate its stability. The simulation results show the limitations of the existing stability criteria for dynamic gaits and indicate that the criterion proposed in this paper can accurately and efficiently evaluate the stability of a quadruped robot using such gaits. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Implementation of Explosion Safety Regulations in Design of a Mobile Robot for Coal Mines
Appl. Sci. 2018, 8(11), 2300; https://doi.org/10.3390/app8112300 - 19 Nov 2018
Cited by 8 | Viewed by 2007
Abstract
The article focuses on specific challenges of the design of a reconnaissance mobile robotic system aimed for inspection in underground coal mine areas after a catastrophic event. Systems that are designated for these conditions must meet specific standards and regulations. In this paper [...] Read more.
The article focuses on specific challenges of the design of a reconnaissance mobile robotic system aimed for inspection in underground coal mine areas after a catastrophic event. Systems that are designated for these conditions must meet specific standards and regulations. In this paper is discussed primarily the main conception of meeting explosion safety regulations of European Union 2014/34/EU (also called ATEX—from French “Appareils destinés à être utilisés en ATmosphères Explosives”) for Group I (equipment intended for use in underground mines) and Category M1 (equipment designed for operation in the presence of an explosive atmosphere). An example of a practical solution is described on main subsystems of the mobile robot TeleRescuer—a teleoperated robot with autonomy functions, a sensory subsystem with multiple cameras, three-dimensional (3D) mapping and sensors for measurement of gas concentration, airflow, relative humidity, and temperatures. Explosion safety is ensured according to the Technical Report CLC/TR 60079-33 “s” by two main independent protections—mechanical protection (flameproof enclosure) and electrical protection (automatic methane detector that disconnects power when methane breaches the enclosure and gets inside the robot body). Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
Mobile Robot Path Planning with a Non-Dominated Sorting Genetic Algorithm
Appl. Sci. 2018, 8(11), 2253; https://doi.org/10.3390/app8112253 - 15 Nov 2018
Cited by 15 | Viewed by 2617
Abstract
In many areas, such as mobile robots, video games and driverless vehicles, path planning has always attracted researchers’ attention. In the field of mobile robotics, the path planning problem is to plan one or more viable paths to the target location from the [...] Read more.
In many areas, such as mobile robots, video games and driverless vehicles, path planning has always attracted researchers’ attention. In the field of mobile robotics, the path planning problem is to plan one or more viable paths to the target location from the starting position within a given obstacle space. Evolutionary algorithms can effectively solve this problem. The non-dominated sorting genetic algorithm (NSGA-II) is currently recognized as one of the evolutionary algorithms with robust optimization capabilities and has solved various optimization problems. In this paper, NSGA-II is adopted to solve multi-objective path planning problems. Three objectives are introduced. Besides the usual selection, crossover and mutation operators, some practical operators are applied. Moreover, the parameters involved in the algorithm are studied. Additionally, another evolutionary algorithm and quality metrics are employed for examination. Comparison results demonstrate that non-dominated solutions obtained by the algorithm have good characteristics. Subsequently, the path corresponding to the knee point of non-dominated solutions is shown. The path is shorter, safer and smoother. This path can be adopted in the later decision-making process. Finally, the above research shows that the revised algorithm can effectively solve the multi-objective path planning problem in static environments. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
A Graph Representation Composed of Geometrical Components for Household Furniture Detection by Autonomous Mobile Robots
Appl. Sci. 2018, 8(11), 2234; https://doi.org/10.3390/app8112234 - 13 Nov 2018
Cited by 2 | Viewed by 1363
Abstract
This study proposes a framework to detect and recognize household furniture using autonomous mobile robots. The proposed methodology is based on the analysis and integration of geometric features extracted over 3D point clouds. A relational graph is constructed using those features to model [...] Read more.
This study proposes a framework to detect and recognize household furniture using autonomous mobile robots. The proposed methodology is based on the analysis and integration of geometric features extracted over 3D point clouds. A relational graph is constructed using those features to model and recognize each piece of furniture. A set of sub-graphs corresponding to different partial views allows matching the robot’s perception with partial furniture models. A reduced set of geometric features is employed: horizontal and vertical planes and the legs of the furniture. These features are characterized through their properties, such as: height, planarity and area. A fast and linear method for the detection of some geometric features is proposed, which is based on histograms of 3D points acquired from an RGB-D camera onboard the robot. Similarity measures for geometric features and graphs are proposed, as well. Our proposal has been validated in home-like environments with two different mobile robotic platforms; and partially on some 3D samples of a database. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
A Novel Approach for a Inverse Kinematics Solution of a Redundant Manipulator
Appl. Sci. 2018, 8(11), 2229; https://doi.org/10.3390/app8112229 - 12 Nov 2018
Cited by 24 | Viewed by 2196
Abstract
Kinematically-redundant manipulators present considerable difficulties, especially from the view of control. A high number of degrees of freedom are used to control so-called secondary tasks in order to optimize manipulator motion. This paper introduces a new algorithm for the control of kinematically-redundant manipulator [...] Read more.
Kinematically-redundant manipulators present considerable difficulties, especially from the view of control. A high number of degrees of freedom are used to control so-called secondary tasks in order to optimize manipulator motion. This paper introduces a new algorithm for the control of kinematically-redundant manipulator considering three secondary tasks, namely a joint limit avoidance task, a kinematic singularities avoidance task, and an obstacle avoidance task. For path planning of end-effector from start to goal point, the potential field method is used. The final inverse kinematic model is designed by a Jacobian-based method considering weight matrices in order to prioritize particular tasks. Our approach is based on the flexible behavior of priority value due to the acceleration of numerical simulation. The results of the simulations show the advantage of our approach, which results in a significant decrease of computing time. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
A Real-Time Hydrodynamic-Based Obstacle Avoidance System for Non-holonomic Mobile Robots with Curvature Constraints
Appl. Sci. 2018, 8(11), 2144; https://doi.org/10.3390/app8112144 - 02 Nov 2018
Cited by 4 | Viewed by 1644
Abstract
The harmonic potential field of an incompressible nonviscous fluid governed by the Laplace’s Equation has shown its potential for being beneficial to autonomous unmanned vehicles to generate smooth, natural-looking, and predictable paths for obstacle avoidance. The streamlines generated by the boundary value problem [...] Read more.
The harmonic potential field of an incompressible nonviscous fluid governed by the Laplace’s Equation has shown its potential for being beneficial to autonomous unmanned vehicles to generate smooth, natural-looking, and predictable paths for obstacle avoidance. The streamlines generated by the boundary value problem of the Laplace’s Equation have explicit, easily computable, or analytic vector fields as the path tangent or robot heading specification without the waypoints and higher order path characteristics. We implemented an obstacle avoidance approach with a focus on curvature constraint for a non-holonomic mobile robot regarded as a particle using curvature-constrained streamlines and streamline changing via pure pursuit. First, we use the potential flow field around a circle to derive three primitive curvature-constrained paths to avoid single obstacles. Furthermore, the pure pursuit controller is implemented to achieve a smooth transition between the streamline paths in the environment with multiple obstacles. In addition to comparative simulations, a proof of concept experiment implemented on a two-wheel driving mobile robot with range sensors validates the practical usefulness of the integrated system that is able to navigate smoothly and safely among multiple cylinder obstacles. The computational requirement of the obstacle avoidance system takes advantage of an a priori selection of fast computing primitive streamline paths, thus, making the system able to generate online a feasible path with a lower maximum curvature that does not violate the curvature constraint. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
A G3-Continuous Extend Procedure for Path Planning of Mobile Robots with Limited Motion Curvature and State Constraints
Appl. Sci. 2018, 8(11), 2127; https://doi.org/10.3390/app8112127 - 02 Nov 2018
Cited by 8 | Viewed by 1463
Abstract
Provably correct and computationally efficient path planning in the presence of various constraints is essential for autonomous driving and agile maneuvering of mobile robots. In this paper, we consider the planning of G 3-continuous planar paths with continuous and limited curvature in [...] Read more.
Provably correct and computationally efficient path planning in the presence of various constraints is essential for autonomous driving and agile maneuvering of mobile robots. In this paper, we consider the planning of G 3-continuous planar paths with continuous and limited curvature in a motion environment that is bounded and contains obstacles modeled by a set of (non-convex) polygons. In practice, the curvature constraints often arise from mechanical limitations for the robot, such as limited steering and articulation angles in wheeled robots, or aerodynamic constraints in unmanned aerial vehicles. To solve the planning problem under those stringent constraints, we improve upon known path primitives, such as Reeds–Shepp (RS) and CC-steer (curvature-continuous) paths. Given the initial and final robot configuration, we developed extend-procedure computing paths that can approximate RS paths with arbitrary precision, but guaranteeing G 3-continuity. We show that satisfaction of all stated path constraints is guaranteed and, contrary to many other methods known from the literature, the method of checking for collisions between the planned path and obstacles is given by a closed-form analytic expression. Furthermore, we demonstrate that our approach is not conservative, i.e., it allows for precise maneuvers in tight environments under the assumption of a rectangular robot footprint. The presented extend procedure can be integrated into various motion-planning algorithms available in the literature. In particular, we utilized the Rapidly exploring Random Trees (RRT*) algorithm in conjunction with our extend procedure to demonstrate its feasibility in motion environments of nontrivial complexity and low computational cost in comparison to a G 3-continuous extend procedure based on η 3-splines. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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Article
The Dynamic Coupling Analysis for All-Wheel-Drive Climbing Robot Based on Safety Recovery Mechanism Model
Appl. Sci. 2018, 8(11), 2123; https://doi.org/10.3390/app8112123 - 01 Nov 2018
Cited by 5 | Viewed by 1925
Abstract
Cable is one of the most important parts on cable-stayed bridges. Its safety is very important. The aim of this study is to design an all-wheel-drive climbing robot based on safety recovery mechanism model for automatic inspection of bridge cables. For this purpose, [...] Read more.
Cable is one of the most important parts on cable-stayed bridges. Its safety is very important. The aim of this study is to design an all-wheel-drive climbing robot based on safety recovery mechanism model for automatic inspection of bridge cables. For this purpose, a model of a three-wheel-drive climbing robot with high-altitude safety recovery mechanism is constructed and the basic performances such as climbing ability and anti-skidding properties are analyzed. Secondly, by employing the finite element method, natural frequency of the robot is calculated and that of a cable with concentrated masses is obtained through use of the Rayleigh quotient. Based on the mentioned quantities, the dynamic characteristics of the robot–cable system are further analyzed. In order to verify the climbing ability of the designed robot, a prototype of the robot is made, a robot testing platform is established and the climbing & loading experiments of the robot are carried out. The experiment results illustrated that the robot can carry a payload of 10 kg and safely return along the cable under the influences of inertial force. Full article
(This article belongs to the Special Issue Advanced Mobile Robotics)
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