Topic Editors

Department of Management and Engineering, University of Padova, 36100 Vicenza, Italy

Motion Planning and Control for Robotics

Abstract submission deadline
closed (31 December 2021)
Manuscript submission deadline
closed (31 March 2022)
Viewed by
167009

Topic Information

Dear colleagues,

The scope of this Topic Issue (TI) is to collect the most recent and cutting-edge developments in the challenging field of motion planning and control in robotic systems. Papers providing original results with new theoretical studies as well as experimental applications on these topics, and to those closely related, are welcome.

As for the issue of the motion planning of robotic systems, the following main topics are covered:

  • Optimal motion planning;
  • Model-based motion planning;
  • Motion planning based on artificial intelligence;
  • Motion planning for vibration suppression;
  • Motion planning for energy saving;
  • Obstacle avoidance;
  • Multi-agent motion planning.

From the point of view of the motion control of robotic systems, the following main topics are covered:

  • Feedback approaches to motion control;
  • Feedforward motion control;
  • Vibration control in robots and manipulators;
  • Impedance control;
  • Multi-agent motion control;
  • Human–robot interaction control.

Other issues closely related to the previous ones (such as modeling approaches, numerical methods suitable for motion planning and control, dynamic structural optimization devoted to control) are also welcome.

Dr. Dario Richiedei
Topic Editor

Keywords

  • robotics
  • mechatronics
  • industrial robots
  • cable robots
  • mobile robots
  • motion planning
  • trajectory planning
  • path planning
  • obstacle avoidance
  • motion control
  • vibration control
  • impedance control
  • multi-agent robot control
  • feedforward control
  • inverse dynamics

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Sciences
applsci
2.5 5.3 2011 17.8 Days CHF 2400
Robotics
robotics
2.9 6.7 2012 17.7 Days CHF 1800
Actuators
actuators
2.2 3.9 2012 16.5 Days CHF 2400
Machines
machines
2.1 3.0 2013 15.6 Days CHF 2400
Applied Mechanics
applmech
- 2.3 2020 21.4 Days CHF 1200

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Published Papers (41 papers)

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14 pages, 663 KiB  
Article
Path-Following and Obstacle Avoidance Control of Nonholonomic Wheeled Mobile Robot Based on Deep Reinforcement Learning
by Xiuquan Cheng, Shaobo Zhang, Sizhu Cheng, Qinxiang Xia and Junhao Zhang
Appl. Sci. 2022, 12(14), 6874; https://doi.org/10.3390/app12146874 - 7 Jul 2022
Cited by 9 | Viewed by 2987
Abstract
In this paper, a novel path-following and obstacle avoidance control method is given for nonholonomic wheeled mobile robots (NWMRs), based on deep reinforcement learning. The model for path-following is investigated first, and then applied to the proposed reinforcement learning control strategy. The proposed [...] Read more.
In this paper, a novel path-following and obstacle avoidance control method is given for nonholonomic wheeled mobile robots (NWMRs), based on deep reinforcement learning. The model for path-following is investigated first, and then applied to the proposed reinforcement learning control strategy. The proposed control method can achieve path-following control through interacting with the environment of the set path. The path-following control method is mainly based on the design of the state and reward function in the training of the reinforcement learning. For extra obstacle avoidance problems in following, the state and reward function is redesigned by utilizing both distance and directional perspective aspects, and a minimum representative value is proposed to deal with the occurrence of multiple obstacles in the path-following environment. Through the reinforcement learning algorithm deep deterministic policy gradient (DDPG), the NWMR can gradually achieve the path it is required to follow and avoid the obstacles in simulation experiments, and the effectiveness of the proposed algorithm is verified. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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26 pages, 1250 KiB  
Article
A Fast and Close-to-Optimal Receding Horizon Control for Trajectory Generation in Dynamic Environments
by Khoi Hoang-Dinh, Marion Leibold and Dirk Wollherr
Robotics 2022, 11(4), 72; https://doi.org/10.3390/robotics11040072 - 6 Jul 2022
Cited by 3 | Viewed by 2573
Abstract
This paper presents a new approach for the optimal trajectory planning of nonlinear systems in a dynamic environment. Given the start and end goals with an objective function, the problem is to find an optimal trajectory from start to end that minimizes the [...] Read more.
This paper presents a new approach for the optimal trajectory planning of nonlinear systems in a dynamic environment. Given the start and end goals with an objective function, the problem is to find an optimal trajectory from start to end that minimizes the objective while taking into account the changes in the environment. One of the main challenges here is that the optimal control sequence needs to be computed in a limited amount of time and needs to be adapted on-the-fly. The control method presented in this work has two stages: the first-order gradient algorithm is used at the beginning to compute an initial guess of the control sequence that satisfies the constraints but is not yet optimal; then, sequential action control is used to optimize only the portion of the control sequence that will be applied on the system in the next iteration. This helps to reduce the computational effort while still being optimal with regard to the objective; thus, the proposed approach is more applicable for online computation as well as dealing with dynamic environments. We also show that under mild conditions, the proposed controller is asymptotically stable. Different simulated results demonstrate the capability of the controller in terms of solving various tracking problems for different systems under the existence of dynamic obstacles. The proposed method is also compared to the related indirect optimal control approach and sequential action control in terms of cost and computation time to evaluate the improvement of the proposed method. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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13 pages, 3152 KiB  
Article
Online Computation of Time-Optimization-Based, Smooth and Path-Consistent Stop Trajectories for Robots
by Rafael A. Rojas, Andrea Giusti and Renato Vidoni
Robotics 2022, 11(4), 70; https://doi.org/10.3390/robotics11040070 - 1 Jul 2022
Cited by 2 | Viewed by 2336
Abstract
Enforcing the cessation of motion is a common action in robotic systems to avoid the damage that the robot can exert on itself, its environment or, in shared environments, people. This procedure raises two main concerns, which are addressed in this paper. On [...] Read more.
Enforcing the cessation of motion is a common action in robotic systems to avoid the damage that the robot can exert on itself, its environment or, in shared environments, people. This procedure raises two main concerns, which are addressed in this paper. On the one hand, the stopping procedure should respect the collision free path computed by the motion planner. On the other hand, a sudden stop may produce large current peaks and challenge the limits of the motor’s control capabilities, as well as degrading the mechanical performance of the system, i.e., increased wear. To address these concerns, we propose a novel method to enforce a mechanically feasible, smooth and path-consistent stop of the robot based on a time-minimization algorithm. We present a numerical implementation of the method, as well as a numerical study of its complexity and convergence. Finally, an experimental comparison with an off-the-shelf stopping scheme is presented, showing the effectiveness of the proposed method. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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14 pages, 2653 KiB  
Article
Stability and Dynamic Walk Control of Humanoid Robot for Robot Soccer Player
by Rudolf Jánoš, Marek Sukop, Ján Semjon, Peter Tuleja, Peter Marcinko, Martin Kočan, Maksym Grytsiv, Marek Vagaš, Ľubica Miková and Tatiana Kelemenová
Machines 2022, 10(6), 463; https://doi.org/10.3390/machines10060463 - 10 Jun 2022
Cited by 10 | Viewed by 3655
Abstract
Robotic football with humanoid robots is a multidisciplinary field connecting several scientific fields. A challenging task in the design of a humanoid robot for the AndroSot and HuroCup competitions is the realization of movement on the field. This study aims to determine a [...] Read more.
Robotic football with humanoid robots is a multidisciplinary field connecting several scientific fields. A challenging task in the design of a humanoid robot for the AndroSot and HuroCup competitions is the realization of movement on the field. This study aims to determine a walking pattern for a humanoid robot with an impact on its dynamic stability and behavior. The design of the proposed technical concept depends on its stability management mechanism, walking speed and such factors as the chosen stability approaches. The humanoid robot and its versatility, along with the adaptability of the terrain, are somewhat limited due to the complexity of the walking principle and the control of the robot’s movement itself. The technical concept uses dynamic stability as the potential force of the inertial bodies and their parts so that the humanoid robot does not overturn. The total height of the robot according to the rules of the competition will be 50 cm. In the performed experiment, only the lower part of the humanoid robot with added weight was considered, which is more demanding due to the non-use of the upper limbs for stabilization. The performed experiment verified the correctness of the design, where the torso of the robot performed eight steps in inclinations of a roll angle +4/−2° and a pitch angle +4/−6°. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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20 pages, 6969 KiB  
Article
An Adaptive and Bounded Controller for Formation Control of Multi-Agent Systems with Communication Break
by Zhigang Xiong, Zhong Liu, Yasong Luo and Jiawei Xia
Appl. Sci. 2022, 12(11), 5602; https://doi.org/10.3390/app12115602 - 31 May 2022
Cited by 2 | Viewed by 1579
Abstract
Aiming at maneuvering, input saturation, and communication interference in the controller design for formation control multi-agent systems, a novel nonlinear bounded controller is proposed. Based on coordinates transformation, reference information is processed, and nonlinear effects of maneuvering are analyzed. Then a nonlinear controller [...] Read more.
Aiming at maneuvering, input saturation, and communication interference in the controller design for formation control multi-agent systems, a novel nonlinear bounded controller is proposed. Based on coordinates transformation, reference information is processed, and nonlinear effects of maneuvering are analyzed. Then a nonlinear controller is established with graph theory, consensus algorithm, and Lyapunov method, which guarantee the stability of the controller. For input saturation avoidance, adaptive parameters are put forward with the Lyapunov function. Considering the communication breaks, various conditions of the sensing graph are discussed for stable formation control, and a dynamic programming regulator is proposed for unknown position reference needed for formation keeping. Comparison with the traditional consensus method is provided in numerical simulation to verify the stability and feasibility of the proposed strategy. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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19 pages, 2546 KiB  
Article
HDPP: High-Dimensional Dynamic Path Planning Based on Multi-Scale Positioning and Waypoint Refinement
by Jingyao Wang, Xiaogang Ruan and Jing Huang
Appl. Sci. 2022, 12(9), 4695; https://doi.org/10.3390/app12094695 - 6 May 2022
Cited by 3 | Viewed by 1927
Abstract
Algorithms such as RRT (Rapidly exploring random tree), A* and their variants have been widely used in the field of robot path planning. A lot of work has shown that these detectors are unable to carry out effective and stable results for moving [...] Read more.
Algorithms such as RRT (Rapidly exploring random tree), A* and their variants have been widely used in the field of robot path planning. A lot of work has shown that these detectors are unable to carry out effective and stable results for moving objects in high-dimensional space, which generate a large number of multi-dimensional corner points. Although some filtering mechanisms (such as splines and valuation functions) reduce the calculation scale, the chance of collision is increased, which is fatal to robots. In order to generate fewer but more effective and stable feature points, we propose a novel multi-scale positioning method to plan the motion of the high-dimensional target. First, a multi-scale feature extraction and refinement scheme for waypoint navigation and positioning is proposed to find the corner points that are more important to the planning, and gradually eliminate the unnecessary redundant points. Then, in order to obtain a stable planning effect, we balance the gradient of corner point classification detection to avoid over-optimizing some of them during the training phase. In addition, considering the maintenance cost of the robot in actual operation, we pay attention to the mechanism of anti-collision in the model design. Our approach can achieve a complete obstacle avoidance rate for high-dimensional space simulation and physical manipulators, and also work well in low-dimensional space for path planning. The experimental results demonstrate the superiority of our approach through a comparison with state-of-the-art models. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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16 pages, 6847 KiB  
Article
Dual-Modal Hybrid Control for an Upper-Limb Rehabilitation Robot
by Guang Feng, Jiaji Zhang, Guokun Zuo, Maoqin Li, Dexin Jiang and Lei Yang
Machines 2022, 10(5), 324; https://doi.org/10.3390/machines10050324 - 29 Apr 2022
Cited by 11 | Viewed by 2954
Abstract
The recovery treatment of motor dysfunction plays a crucial role in rehabilitation therapy. Rehabilitation robots are partially or fully replacing therapists in assisting patients in exercise by advantage of robot technologies. However, the rehabilitation training system is not yet intelligent enough to provide [...] Read more.
The recovery treatment of motor dysfunction plays a crucial role in rehabilitation therapy. Rehabilitation robots are partially or fully replacing therapists in assisting patients in exercise by advantage of robot technologies. However, the rehabilitation training system is not yet intelligent enough to provide suitable exercise modes based on the exercise intentions of patients with different motor abilities. In this paper, a dual-modal hybrid self-switching control strategy (DHSS) is proposed to automatically determine the exercise mode of patients, i.e., passive and assistive exercise mode. In this strategy, the potential field method and the ADRC position control are employed to plan trajectories and assist patients’ training. Dual-modal self-switching rules based on the motor and impulse information of patients are presented to identify patients’ motor abilities. Finally, the DHSS assisted five subjects in performing the training with an average deviation error of less than 2 mm in both exercise modes. The experimental results demonstrate that the muscle activation of the subjects differed significantly in different modes. It also verifies that DHSS is reasonable and effective, which helps patients to train independently without therapists. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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22 pages, 10700 KiB  
Article
Active Assistive Design and Multiaxis Self-Tuning Control of a Novel Lower Limb Rehabilitation Exoskeleton
by Cheng-Tang Pan, Ming-Chan Lee, Jhih-Syuan Huang, Chun-Chieh Chang, Zheng-Yu Hoe and Kuan-Ming Li
Machines 2022, 10(5), 318; https://doi.org/10.3390/machines10050318 - 28 Apr 2022
Cited by 5 | Viewed by 2880
Abstract
This paper presented the mechanical design and control of a lower limb rehabilitation exoskeleton named “the second lower limb rehabilitation exoskeleton (LLRE-II)”. The exoskeleton with a lightweight mechanism comprises a 16-cm stepless adjustable thigh and calf rod. The LLRE-II weighs less than 16 [...] Read more.
This paper presented the mechanical design and control of a lower limb rehabilitation exoskeleton named “the second lower limb rehabilitation exoskeleton (LLRE-II)”. The exoskeleton with a lightweight mechanism comprises a 16-cm stepless adjustable thigh and calf rod. The LLRE-II weighs less than 16 kg and has four degrees of freedom on each leg, including the waist, hip, knee, and ankle, which ensures fitted wear and comfort. Motors and harmonic drives were installed on the joints of the hip and knee to operate the exoskeleton. Meanwhile, master and slave motor controllers were programmed using a Texas Instruments microcontroller (TMS320F28069) for the walking gait commands and evaluation boards (TMS320F28069/DRV8301) of the joints. A self-tuning multiaxis control system was developed, and the performance of the controller was investigated through experiments. The experimental results showed that the mechanical design and control system exhibit adequate performance. Trajectory tracking errors were eliminated, and the root mean square errors reduced from 6.45 to 1.22 and from 4.15 to 3.09 for the hip and knee, respectively. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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16 pages, 5709 KiB  
Article
Design of a Parallel Quadruped Robot Based on a Novel Intelligent Control System
by Mingying Li, Zhilei Liu, Manfu Wang, Guibing Pang and Hui Zhang
Appl. Sci. 2022, 12(9), 4358; https://doi.org/10.3390/app12094358 - 25 Apr 2022
Cited by 10 | Viewed by 3438
Abstract
In order to make a robot track a desired trajectory with high precision and steady gait, a novel intelligent controller was designed based on a new mechanical structure and optimized foot trajectory. Kinematics models in terms of the D-H method were established to [...] Read more.
In order to make a robot track a desired trajectory with high precision and steady gait, a novel intelligent controller was designed based on a new mechanical structure and optimized foot trajectory. Kinematics models in terms of the D-H method were established to analyze the relationship between the angle of the driving joint and the foot position. Inspired by a dog’s diagonal trot on a flat terrain, foot trajectory planning in the swing and support phases without impact were fulfilled based on the compound cycloid improved by the Bézier curve. Both the optimized cascade proportional–integral–derivative (PID) control system and improved fuzzy adaptive PID control system were applied to realize the stable operation of a quadruped robot, and their parameters were optimized by the sparrow search algorithm. The convergence speed and accuracy of the sparrow search algorithm were verified by comparing with the moth flame optimization algorithm and particle swarm optimization algorithm. Finally, a co-simulation with MATLAB and ADAMS was utilized to compare the effects of the two control systems. The results of both displacement and velocity exhibit that the movement of a quadruped bionic robot with fuzzy adaptive PID control systems optimized by the sparrow search algorithm possessed better accuracy and stability than cascade PID control systems. The motion process of the quadruped robot in the co-simulation process also demonstrates the effectiveness of the designed mechanical structure and control system. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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17 pages, 3723 KiB  
Article
Dynamics Modeling and Adaptive Sliding Mode Control of a Hybrid Condenser Cleaning Robot
by Jiabao Li and Chengjun Wang
Actuators 2022, 11(5), 119; https://doi.org/10.3390/act11050119 - 24 Apr 2022
Cited by 5 | Viewed by 2406
Abstract
This study examines the pose control of the 4-RPU redundant parallel mechanism of a hybrid condenser cleaning robot in response to the poor control accuracy of current cleaning robots. The kinematics of the 4-RPU mechanism is analysed, and its dynamics model is constructed [...] Read more.
This study examines the pose control of the 4-RPU redundant parallel mechanism of a hybrid condenser cleaning robot in response to the poor control accuracy of current cleaning robots. The kinematics of the 4-RPU mechanism is analysed, and its dynamics model is constructed using the virtual work principle. The theoretical calculation and virtual prototype simulation of the constructed model are conducted in MATLAB and ADAMS, which yield basically consistent results, demonstrating the precision of the model. Based on this model, an adaptive sliding mode control method is proposed that can estimate and compensate for parameter uncertainties and load perturbations simultaneously. The system stability is analysed using Lyapunov functions. The results suggest that the adaptive sliding mode control method can significantly reduce the average tracking error of each degree of freedom of the moving platform and exhibits higher control stability and convergence accuracy than the conventional sliding mode control algorithm. This study provides a reference and research basis for attitude control of the cleaning robots affected by uncertainties such as water backlash during operation. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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21 pages, 2235 KiB  
Article
RTSDM: A Real-Time Semantic Dense Mapping System for UAVs
by Zhiteng Li, Jiannan Zhao, Xiang Zhou, Shengxian Wei, Pei Li and Feng Shuang
Machines 2022, 10(4), 285; https://doi.org/10.3390/machines10040285 - 18 Apr 2022
Cited by 8 | Viewed by 3402
Abstract
Intelligent drones or flying robots play a significant role in serving our society in applications such as rescue, inspection, agriculture, etc. Understanding the scene of the surroundings is an essential capability for further autonomous tasks. Intuitively, knowing the self-location of the UAV and [...] Read more.
Intelligent drones or flying robots play a significant role in serving our society in applications such as rescue, inspection, agriculture, etc. Understanding the scene of the surroundings is an essential capability for further autonomous tasks. Intuitively, knowing the self-location of the UAV and creating a semantic 3D map is significant for fully autonomous tasks. However, integrating simultaneous localization, 3D reconstruction, and semantic segmentation together is a huge challenge for power-limited systems such as UAVs. To address this, we propose a real-time semantic mapping system that can help a power-limited UAV system to understand its location and surroundings. The proposed approach includes a modified visual SLAM with the direct method to accelerate the computationally intensive feature matching process and a real-time semantic segmentation module at the back end. The semantic module runs a lightweight network, BiSeNetV2, and performs segmentation only at key frames from the front-end SLAM task. Considering fast navigation and the on-board memory resources, we provide a real-time dense-map-building module to generate an OctoMap with the segmented semantic map. The proposed system is verified in real-time experiments on a UAV platform with a Jetson TX2 as the computation unit. A frame rate of around 12 Hz, with a semantic segmentation accuracy of around 89% demonstrates that our proposed system is computationally efficient while providing sufficient information for fully autonomous tasks such as rescue, inspection, etc. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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19 pages, 1960 KiB  
Article
Study of Variational Inference for Flexible Distributed Probabilistic Robotics
by Malte Rørmose Damgaard, Rasmus Pedersen and Thomas Bak
Robotics 2022, 11(2), 38; https://doi.org/10.3390/robotics11020038 - 24 Mar 2022
Cited by 2 | Viewed by 2806
Abstract
By combining stochastic variational inference with message passing algorithms, we show how to solve the highly complex problem of navigation and avoidance in distributed multi-robot systems in a computationally tractable manner, allowing online implementation. Subsequently, the proposed variational method lends itself to more [...] Read more.
By combining stochastic variational inference with message passing algorithms, we show how to solve the highly complex problem of navigation and avoidance in distributed multi-robot systems in a computationally tractable manner, allowing online implementation. Subsequently, the proposed variational method lends itself to more flexible solutions than prior methodologies. Furthermore, the derived method is verified both through simulations with multiple mobile robots and a real world experiment with two mobile robots. In both cases, the robots share the operating space and need to cross each other’s paths multiple times without colliding. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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14 pages, 2322 KiB  
Article
High-Precision Anti-Interference Control of Direct Drive Components
by Jieji Zheng, Xianliang Jiang, Guangan Ren, Xin Xie and Dapeng Fan
Actuators 2022, 11(3), 95; https://doi.org/10.3390/act11030095 - 19 Mar 2022
Cited by 1 | Viewed by 2548
Abstract
This study presents a compound control algorithm that enhances the servo accuracy and disturbance suppression capability of direct drive components (DDCs). The servo performance of DDCs is easily affected by external disturbance and the deterioration of assembly characteristics due to a lack of [...] Read more.
This study presents a compound control algorithm that enhances the servo accuracy and disturbance suppression capability of direct drive components (DDCs). The servo performance of DDCs is easily affected by external disturbance and the deterioration of assembly characteristics due to a lack of deceleration device. The purpose of this study is to compensate for the impact of external and internal disturbances on the system. First, a linear state space model of the system is established. Second, we analyzed the main factors restricting the performance of DDCs which includes sensor noise, friction and external disturbance. Then, a fractional-order proportional integral (FOPI) controller was used to eliminate the steady-state error caused by the time-invariable disturbance which can also improve the system’s anti-interference capability. A state-augmented Kalman filter (SAKF) was proposed to suppress the quantization noise and compensate for the time-varying disturbances simultaneously. The effectiveness of the proposed compound algorithm was demonstrated by comparative experiments, demonstrating a maximum 89.34% improvement. The experimental results show that, compared with the traditional PI controller, the FOPISAKF controller can not only improve the tracking accuracy of the system, but also enhance the disturbance suppression ability. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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13 pages, 8701 KiB  
Article
PSTO: Learning Energy-Efficient Locomotion for Quadruped Robots
by Wangshu Zhu and Andre Rosendo
Machines 2022, 10(3), 185; https://doi.org/10.3390/machines10030185 - 4 Mar 2022
Cited by 4 | Viewed by 3249
Abstract
Energy efficiency is critical for the locomotion of quadruped robots. However, energy efficiency values found in simulations do not transfer adequately to the real world. To address this issue, we present a novel method, named Policy Search Transfer Optimization (PSTO), which combines deep [...] Read more.
Energy efficiency is critical for the locomotion of quadruped robots. However, energy efficiency values found in simulations do not transfer adequately to the real world. To address this issue, we present a novel method, named Policy Search Transfer Optimization (PSTO), which combines deep reinforcement learning and optimization to create energy-efficient locomotion for quadruped robots in the real world. The deep reinforcement learning and policy search process are performed by the TD3 algorithm and the policy is transferred to the open-loop control trajectory further optimized by numerical methods, and conducted on the robot in the real world. In order to ensure the high uniformity of the simulation results and the behavior of the hardware platform, we introduce and validate the accurate model in simulation including consistent size and fine-tuning parameters. We then validate those results with real-world experiments on the quadruped robot Ant by executing dynamic walking gaits with different leg lengths and numbers of amplifications. We analyze the results and show that our methods can outperform the control method provided by the state-of-the-art policy search algorithm TD3 and sinusoid function on both energy efficiency and speed. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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14 pages, 3088 KiB  
Article
Balance Control of a Quadruped Robot Based on Foot Fall Adjustment
by Wenkai Sun, Xiaojie Tian, Yong Song, Bao Pang, Xianfeng Yuan and Qingyang Xu
Appl. Sci. 2022, 12(5), 2521; https://doi.org/10.3390/app12052521 - 28 Feb 2022
Cited by 11 | Viewed by 5038
Abstract
To balance the diagonal gait of a quadruped robot, a dynamic balance control method is presented to improve the stability of the quadruped robot by adjusting its foot position. We set up a trunk-based coordinate system and a hip-based local coordinate system for [...] Read more.
To balance the diagonal gait of a quadruped robot, a dynamic balance control method is presented to improve the stability of the quadruped robot by adjusting its foot position. We set up a trunk-based coordinate system and a hip-based local coordinate system for the quadruped robot, established the kinematics equation of the robot, and designed a reasonable initial diagonal gait through the spring inverted pendulum model. The current trunk posture of the quadruped robot is obtained by collecting the data of its pitch and roll angle, and the foot position is predicted according to the current posture and initial gait of the quadruped robot. To reduce the impact of one leg landing on the ground and increase the stability of the quadruped robot, we adjust the landing point of the robot according to the landing time difference between the diagonal legs. The proposed method can adjust the body in such scenarios as planar walking and lateral impact resistance. It can reduce the disturbance during the robot motion and make the robot move smoothly. The validity of this method is verified by simulation experiments. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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15 pages, 7800 KiB  
Article
Local Path-Planning Simulation and Driving Test of Electric Unmanned Ground Vehicles for Cooperative Mission with Unmanned Aerial Vehicles
by Mingeuk Kim, Seungjin Yoo, Dongwook Lee and Geun-Ho Lee
Appl. Sci. 2022, 12(5), 2326; https://doi.org/10.3390/app12052326 - 23 Feb 2022
Cited by 3 | Viewed by 1963
Abstract
Recently, various studies related to the development of unmanned vehicles have been conducted around the world. In particular, unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) have been developed and utilized for various purposes. In this study, we developed a method for [...] Read more.
Recently, various studies related to the development of unmanned vehicles have been conducted around the world. In particular, unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) have been developed and utilized for various purposes. In this study, we developed a method for the path generation of UGVs in a system in which one operator controls many different types of unmanned vehicles. In the driving control system (DCS), it is necessary to process sensor data such as GPS/INS and LiDAR when generating a path by receiving the target waypoint from the ground control station. In addition, the DCS must upload the current location, posture, state, etc., as well as save driving log. Therefore, in order to recognize obstacles in real time and generate a path, a safe path generation algorithm with a short computation time is required. Among the various path generation methods, the potential field algorithm was selected, and the algorithm was modified to reduce the computation time. The computation time before and after modification of the algorithm was obtained and compared through simulation, and the algorithm was verified through application to an actual system by performing an obstacle avoidance experiment and a simultaneous control experiment for two UGVs. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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27 pages, 1737 KiB  
Review
A Comprehensive Survey of Visual SLAM Algorithms
by Andréa Macario Barros, Maugan Michel, Yoann Moline, Gwenolé Corre and Frédérick Carrel
Robotics 2022, 11(1), 24; https://doi.org/10.3390/robotics11010024 - 10 Feb 2022
Cited by 208 | Viewed by 34110
Abstract
Simultaneous localization and mapping (SLAM) techniques are widely researched, since they allow the simultaneous creation of a map and the sensors’ pose estimation in an unknown environment. Visual-based SLAM techniques play a significant role in this field, as they are based on a [...] Read more.
Simultaneous localization and mapping (SLAM) techniques are widely researched, since they allow the simultaneous creation of a map and the sensors’ pose estimation in an unknown environment. Visual-based SLAM techniques play a significant role in this field, as they are based on a low-cost and small sensor system, which guarantees those advantages compared to other sensor-based SLAM techniques. The literature presents different approaches and methods to implement visual-based SLAM systems. Among this variety of publications, a beginner in this domain may find problems with identifying and analyzing the main algorithms and selecting the most appropriate one according to his or her project constraints. Therefore, we present the three main visual-based SLAM approaches (visual-only, visual-inertial, and RGB-D SLAM), providing a review of the main algorithms of each approach through diagrams and flowcharts, and highlighting the main advantages and disadvantages of each technique. Furthermore, we propose six criteria that ease the SLAM algorithm’s analysis and consider both the software and hardware levels. In addition, we present some major issues and future directions on visual-SLAM field, and provide a general overview of some of the existing benchmark datasets. This work aims to be the first step for those initiating a SLAM project to have a good perspective of SLAM techniques’ main elements and characteristics. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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20 pages, 5953 KiB  
Article
Multi-Robot Robust Motion Planning based on Model Predictive Priority Contouring Control with Double-Layer Corridors
by Lingli Yu and Zhengjiu Wang
Appl. Sci. 2022, 12(3), 1682; https://doi.org/10.3390/app12031682 - 6 Feb 2022
Viewed by 2269
Abstract
Disturbance poses a major challenge for the safety and real-time performance of robust robot motion planning. To address the disturbance while improving the real-time performance of multi-robot robust motion planning, a model predictive priority contouring control method is proposed. First, an improved conflict-based [...] Read more.
Disturbance poses a major challenge for the safety and real-time performance of robust robot motion planning. To address the disturbance while improving the real-time performance of multi-robot robust motion planning, a model predictive priority contouring control method is proposed. First, an improved conflict-based search (ICBS) planner is utilized to plan reference paths. The low-level planner of the conflicted-based search (CBS) planner is replaced by the hybrid A* planner and reference paths are adopted as an initial guess of model predictive priority contouring control. Second, double-layer corridors are proposed to provide safety guarantees, which include static-layer corridors and dynamic-layer corridors. The static-layer corridors are generated based on reference paths and the dynamic-layer corridors are generated based on the relative positions and velocities of robots. The double-layer corridors are applied as safety constraints of model predictive priority contouring control. Third, a prioritization mechanism is devised to improve computational efficiency. Priorities are assigned according to each robot’s task completion percentage. Based on the assigned priority, multiple robots are grouped, and each group executes the model predictive priority contouring control algorithm to acquire trajectories. Finally, our method is compared with the centralized method and the soft constraint-based DMPC. Simulations verify the effectiveness and real-time performance of our approach. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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16 pages, 4515 KiB  
Article
Assist-As-Needed Control Strategy of Bilateral Upper Limb Rehabilitation Robot Based on GMM
by Maoqin Li, Jiaji Zhang, Guokun Zuo, Guang Feng and Xueliang Zhang
Machines 2022, 10(2), 76; https://doi.org/10.3390/machines10020076 - 21 Jan 2022
Cited by 17 | Viewed by 3689
Abstract
Robotic-assisted rehabilitation therapy has been shown to be effective in improving upper limb motor function and the daily behavior of patients with motor dysfunction. At present, the majority of upper limb rehabilitation robots can only move in the two-dimensional plane, and cannot adjust [...] Read more.
Robotic-assisted rehabilitation therapy has been shown to be effective in improving upper limb motor function and the daily behavior of patients with motor dysfunction. At present, the majority of upper limb rehabilitation robots can only move in the two-dimensional plane, and cannot adjust the assistance mode in real-time according to the patient’s rehabilitation needs. In this paper, according to the shortcomings of the current rehabilitation robot only moving in the two-dimensional plane, a type of bilateral mirror upper limb rehabilitation robot structure with the healthy side assisting the affected side is proposed. This can move in three-dimensional space. Additionally, an assist-as-needed (AAN) control strategy for upper limb rehabilitation training is proposed based on the bilateral upper limb rehabilitation robot. The control strategy adopts Gaussian Mixture Model (GMM) and impedance controller to maximize the patient’s rehabilitation effect. In the task’s design, there is no need to rely on the assistance of the therapist, only the patients who completed the task independently. GMM guides the rehabilitation robot to provide different assistance for the patients at different task stages and induces the patients to complete the rehabilitation training independently by judging the extent to which the patients can complete the task. Furthermore, in this paper, the effectiveness of the proposed control strategy was verified by three volunteers participating in a two-dimensional task. The experimental results show that the proposed AAN control strategy can effectively provide appropriate assistance according to the classification stage of the interaction between the patients and the rehabilitation robot, and thus, patients can better achieve the rehabilitation effect during the rehabilitation task as much as possible. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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19 pages, 6013 KiB  
Article
Path Planning Strategy for a Manipulator Based on a Heuristically Constructed Network
by Junting Fei, Gang Chen, Qingxuan Jia, Changchun Liang and Ruiquan Wang
Machines 2022, 10(2), 71; https://doi.org/10.3390/machines10020071 - 19 Jan 2022
Cited by 2 | Viewed by 2272
Abstract
Collision-free path planning of manipulators is becoming indispensable for space exploration and on-orbit operation. Manipulators in these scenarios are restrained in terms of computing resources and storage, so the path planning method used in such tasks is usually limited in its operating time [...] Read more.
Collision-free path planning of manipulators is becoming indispensable for space exploration and on-orbit operation. Manipulators in these scenarios are restrained in terms of computing resources and storage, so the path planning method used in such tasks is usually limited in its operating time and the amount of data transmission. In this paper, a heuristically constructed network (HCN) construction strategy is proposed. The HCN construction contains three steps: determining the number of hub configurations and selecting and connecting hub configurations. Considering the connection time and connectivity of HCN, the number of hub configurations is determined first. The selection of hub configurations includes the division of work space and the optimization of the hub configurations. The work space can be divided by considering comprehensively the similarity among the various configurations within the same region, the dissimilarity among all regions, and the correlation among adjacent regions. The hub configurations can be selected by establishing and solving the optimization model. Finally, these hub configurations are connected to obtain the HCN. The simulation indicates that the path points number and the planning time is decreased by 45.5% and 48.4%, respectively, which verify the correctness and effectiveness of the proposed path planning strategy based on the HCN. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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19 pages, 2782 KiB  
Article
Modified Whale Optimization Algorithm for Multi-Type Combine Harvesters Scheduling
by Wenqiang Yang, Zhile Yang, Yonggang Chen and Zhanlei Peng
Machines 2022, 10(1), 64; https://doi.org/10.3390/machines10010064 - 17 Jan 2022
Cited by 8 | Viewed by 2771
Abstract
The optimal scheduling of multi-type combine harvesters is a crucial topic in improving the operating efficiency of combine harvesters. Due to the NP-hard property of this problem, developing appropriate optimization approaches is an intractable task. The multi-type combine harvesters scheduling problem considered in [...] Read more.
The optimal scheduling of multi-type combine harvesters is a crucial topic in improving the operating efficiency of combine harvesters. Due to the NP-hard property of this problem, developing appropriate optimization approaches is an intractable task. The multi-type combine harvesters scheduling problem considered in this paper deals with the question of how a given set of harvesting tasks should be assigned to each combine harvester, such that the total cost is comprehensively minimized. In this paper, a novel multi-type combine harvesters scheduling problem is first formulated as a constrained optimization problem. Then, a whale optimization algorithm (WOA) including an opposition-based learning search operator, adaptive convergence factor and heuristic mutation, namely, MWOA, is proposed and evaluated based on benchmark functions and comprehensive computational studies. Finally, the proposed intelligent approach is used to solve the multi-type combine harvesters scheduling problem. The experimental results prove the superiority of the MWOA in terms of solution quality and convergence speed both in the benchmark test and for solving the complex multi-type combine harvester scheduling problem. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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17 pages, 5657 KiB  
Article
Effects on Trajectory of a Spear Using Movement of Robotic Fish Equipped with Spear Shooting Mechanism
by Naoki Kawasaki, Kazuki Tonomura, Masashi Ohara, Ayane Shinojima and Yogo Takada
Robotics 2022, 11(1), 14; https://doi.org/10.3390/robotics11010014 - 11 Jan 2022
Viewed by 2789
Abstract
In Japan, the disruption of ecosystems caused by alien fish in lakes and ponds is a major issue. To address this problem, we propose that the robotic fish COMET can assist in alien fish extermination by adding the function of spear shooting. The [...] Read more.
In Japan, the disruption of ecosystems caused by alien fish in lakes and ponds is a major issue. To address this problem, we propose that the robotic fish COMET can assist in alien fish extermination by adding the function of spear shooting. The way of extermination is that when COMET finds an alien fish, let COMET approach an alien fish without being wary it and spear it. In this study, we investigated the spear shooting process under different movement conditions to determine the impact on the accuracy of the trajectory of the spear. The results confirmed that a certain set of conditions can improve the accuracy of hitting the target with a spear using specific movements of the robotic fish. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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29 pages, 8913 KiB  
Article
An Effective Dynamic Path Planning Approach for Mobile Robots Based on Ant Colony Fusion Dynamic Windows
by Liwei Yang, Lixia Fu, Ping Li, Jianlin Mao and Ning Guo
Machines 2022, 10(1), 50; https://doi.org/10.3390/machines10010050 - 9 Jan 2022
Cited by 38 | Viewed by 4995
Abstract
To further improve the path planning of the mobile robot in complex dynamic environments, this paper proposes an enhanced hybrid algorithm by considering the excellent search capability of the ant colony optimization (ACO) for global paths and the advantages of the dynamic window [...] Read more.
To further improve the path planning of the mobile robot in complex dynamic environments, this paper proposes an enhanced hybrid algorithm by considering the excellent search capability of the ant colony optimization (ACO) for global paths and the advantages of the dynamic window approach (DWA) for local obstacle avoidance. Firstly, we establish a new dynamic environment model based on the motion characteristics of the obstacles. Secondly, we improve the traditional ACO from the pheromone update and heuristic function and then design a strategy to solve the deadlock problem. Considering the actual path requirements of the robot, a new path smoothing method is present. Finally, the robot modeled by DWA obtains navigation information from the global path, and we enhance its trajectory tracking capability and dynamic obstacle avoidance capability by improving the evaluation function. The simulation and experimental results show that our algorithm improves the robot’s navigation capability, search capability, and dynamic obstacle avoidance capability in unknown and complex dynamic environments. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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16 pages, 4577 KiB  
Article
Hyper-Redundant Manipulator Capable of Adjusting Its Non-Uniform Curvature with Discrete Stiffness Distribution
by Seongil Kwon, Jeongryul Kim, Yonghwan Moon and Keri Kim
Appl. Sci. 2022, 12(1), 482; https://doi.org/10.3390/app12010482 - 4 Jan 2022
Cited by 3 | Viewed by 2255
Abstract
Hyper-redundant manipulators are widely used in minimally invasive surgery because they can navigate through narrow passages in passive compliance with the human body. Although their stability and dexterity have been significantly improved over the years, we need manipulators that can bend with appropriate [...] Read more.
Hyper-redundant manipulators are widely used in minimally invasive surgery because they can navigate through narrow passages in passive compliance with the human body. Although their stability and dexterity have been significantly improved over the years, we need manipulators that can bend with appropriate curvatures and adapt to complex environments. This paper proposes a design principle for a manipulator capable of adjusting its non-uniform curvature and predicting the bending shape. Rigid segments were serially stacked, and elastic fixtures in the form of flat springs were arranged between hinged-slide joint segments. A manipulator with a diameter of 4.5 mm and a length of 28 mm had been fabricated. A model was established to predict the bending shape through minimum potential energy theory, kinematics, and measured stiffnesses of the flat springs. A comparison of the simulation and experimental results indicated an average position error of 3.82% of the endpoints when compared to the total length. With this modification, the manipulator is expected to be widely used in various fields such as small endoscope systems and single-port robot systems. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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30 pages, 7667 KiB  
Article
Multi-UAV Optimal Mission Assignment and Path Planning for Disaster Rescue Using Adaptive Genetic Algorithm and Improved Artificial Bee Colony Method
by Haoting Liu, Jianyue Ge, Yuan Wang, Jiacheng Li, Kai Ding, Zhiqiang Zhang, Zhenhui Guo, Wei Li and Jinhui Lan
Actuators 2022, 11(1), 4; https://doi.org/10.3390/act11010004 - 28 Dec 2021
Cited by 43 | Viewed by 4271
Abstract
An optimal mission assignment and path planning method of multiple unmanned aerial vehicles (UAVs) for disaster rescue is proposed. In this application, the UAVs include the drug delivery UAV, image collection UAV, and communication relay UAV. When implementing the modeling and simulation, first, [...] Read more.
An optimal mission assignment and path planning method of multiple unmanned aerial vehicles (UAVs) for disaster rescue is proposed. In this application, the UAVs include the drug delivery UAV, image collection UAV, and communication relay UAV. When implementing the modeling and simulation, first, three threat sources are built: the weather threat source, transmission tower threat source, and upland threat source. Second, a cost-revenue function is constructed. The flight distance, oil consumption, function descriptions of UAV, and threat source factors above are considered. The analytic hierarchy process (AHP) method is utilized to estimate the weights of cost-revenue function. Third, an adaptive genetic algorithm (AGA) is designed to solve the mission allocation task. A fitness function which considers the current and maximum iteration numbers is proposed to improve the AGA convergence performance. Finally, an optimal path plan between the neighboring mission points is computed by an improved artificial bee colony (IABC) method. A balanced searching strategy is developed to modify the IABC computational effect. Extensive simulation experiments have shown the effectiveness of our method. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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22 pages, 7362 KiB  
Article
Motion Planning of Ground Simulator for Space Instable Target Based on Energy Saving
by Xinlin Bai, Xiwen Li, Zhen Zhao, Mingyi Yang, Zhang Zhang, Zhigang Xu, Mingyang Liu and Qi Xia
Machines 2021, 9(12), 368; https://doi.org/10.3390/machines9120368 - 18 Dec 2021
Cited by 1 | Viewed by 2521
Abstract
In order to achieve the high-precision motion trajectory in ground experiment of space instable target (SIT) while reducing the energy consumption of the motion simulator, a robot motion planning method based on energy saving is proposed. Observable-based ground robot motion experiment system for [...] Read more.
In order to achieve the high-precision motion trajectory in ground experiment of space instable target (SIT) while reducing the energy consumption of the motion simulator, a robot motion planning method based on energy saving is proposed. Observable-based ground robot motion experiment system for SIT is designed and motion planning process is illustrated. Discrete optimization mathematical model of energy consumption of motion simulator is established. The general motion form of the robot joints in ground test is given. The optimal joint path of motion simulator based on energy consumption under discontinuous singularity configuration is solved by constructing the complete energy consumption directed path and Dijkstra algorithm. An improved method by adding the global optimization algorithm is used to decouple the coupled robot joints to obtain the minimum energy consumption path under the continuous singularity configuration of the motion simulator. Simulations are carried out to verify the proposed solution. The simulation data show that total energy saving of motion simulator joints adopting the proposed method under the condition of non-singularity configuration, joints coupled motion with continuous singularity configuration, and coexistence of non-singularity path and continuous singularity path are, respectively, 72.67%, 28.24%, and 62.23%, which proves that the proposed method can meet the requirements of ground motion simulation for SIT and effectively save energy. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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11 pages, 1386 KiB  
Article
Overcoming Kinematic Singularities for Motion Control in a Caster Wheeled Omnidirectional Robot
by Oded Medina and Shlomi Hacohen
Robotics 2021, 10(4), 133; https://doi.org/10.3390/robotics10040133 - 13 Dec 2021
Cited by 4 | Viewed by 3544
Abstract
Omnidirectional planar robots are common these days due to their high mobility, for example in human–robot interactions. The motion of such mechanisms is based on specially designed wheels, which may vary when different terrains are considered. The usage of actuated caster wheels (ACW) [...] Read more.
Omnidirectional planar robots are common these days due to their high mobility, for example in human–robot interactions. The motion of such mechanisms is based on specially designed wheels, which may vary when different terrains are considered. The usage of actuated caster wheels (ACW) may enable the usage of regular wheels. Yet, it is known that an ACW robot with three actuated wheels needs to overcome kinematic singularities. This paper introduces the kinematic model for an ACW omni robot. We present a novel method to overcome the kinematic singularities of the mechanism’s Jacobian matrix by performing the time propagation in the mechanism’s configuration space. We show how the implementation of this method enables the estimation of caster wheels’ swivel angles by tracking the plate’s velocity. We present the mechanism’s kinematics and trajectory tracking in real-world experimentation using a novel robot design. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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21 pages, 5370 KiB  
Article
A Novel, Oriented to Graphs Model of Robot Arm Dynamics
by George Boiadjiev, Evgeniy Krastev, Ivan Chavdarov and Lyubomira Miteva
Robotics 2021, 10(4), 128; https://doi.org/10.3390/robotics10040128 - 28 Nov 2021
Cited by 2 | Viewed by 4635
Abstract
Robotics is an interdisciplinary field and there exist several well-known approaches to represent the dynamics model of a robot arm. The robot arm is an open kinematic chain of links connected through rotational and translational joints. In the general case, it is very [...] Read more.
Robotics is an interdisciplinary field and there exist several well-known approaches to represent the dynamics model of a robot arm. The robot arm is an open kinematic chain of links connected through rotational and translational joints. In the general case, it is very difficult to obtain explicit expressions for the forces and the torques in the equations where the driving torques of the actuators produce desired motion of the gripper. The robot arm control depends significantly on the accuracy of the dynamic model. In the existing literature, the complexity of the dynamic model is reduced by linearization techniques or techniques like machine learning for the identification of unmodelled dynamics. This paper proposes a novel approach for deriving the equations of motion and the actuator torques of a robot arm with an arbitrary number of joints. The proposed approach for obtaining the dynamic model in closed form employs graph theory and the orthogonality principle, a powerful concept that serves as a generalization for the law of conservation of energy. The application of this approach is demonstrated using a 3D-printed planar robot arm with three degrees of freedom. Computer experiments for this robot are executed to validate the dynamic characteristics of the mathematical model of motion obtained by the application of the proposed approach. The results from the experiments are visualized and discussed in detail. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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13 pages, 1107 KiB  
Article
Reinforcement Learning with Dynamic Movement Primitives for Obstacle Avoidance
by Ang Li, Zhenze Liu, Wenrui Wang, Mingchao Zhu, Yanhui Li, Qi Huo and Ming Dai
Appl. Sci. 2021, 11(23), 11184; https://doi.org/10.3390/app112311184 - 25 Nov 2021
Cited by 7 | Viewed by 3372
Abstract
Dynamic movement primitives (DMPs) are a robust framework for movement generation from demonstrations. This framework can be extended by adding a perturbing term to achieve obstacle avoidance without sacrificing stability. The additional term is usually constructed based on potential functions. Although different potentials [...] Read more.
Dynamic movement primitives (DMPs) are a robust framework for movement generation from demonstrations. This framework can be extended by adding a perturbing term to achieve obstacle avoidance without sacrificing stability. The additional term is usually constructed based on potential functions. Although different potentials are adopted to improve the performance of obstacle avoidance, the profiles of potentials are rarely incorporated into reinforcement learning (RL) framework. In this contribution, we present a RL based method to learn not only the profiles of potentials but also the shape parameters of a motion. The algorithm employed is PI2 (Policy Improvement with Path Integrals), a model-free, sampling-based learning method. By using the PI2, the profiles of potentials and the parameters of the DMPs are learned simultaneously; therefore, we can optimize obstacle avoidance while completing specified tasks. We validate the presented method in simulations and with a redundant robot arm in experiments. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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19 pages, 6286 KiB  
Article
GPS Path Tracking Control of Military Unmanned Vehicle Based on Preview Variable Universe Fuzzy Sliding Mode Control
by Houzhong Zhang, Xiangtian Yang, Jiasheng Liang, Xing Xu and Xiaoqiang Sun
Machines 2021, 9(12), 304; https://doi.org/10.3390/machines9120304 - 23 Nov 2021
Cited by 8 | Viewed by 2199
Abstract
In the process of the continuous development and improvement of modern military systems, military unmanned vehicles play an important role in field reconnaissance and strategic deployment. In this paper, the precise tracking algorithm of a military unmanned vehicle, based on GPS navigation, is [...] Read more.
In the process of the continuous development and improvement of modern military systems, military unmanned vehicles play an important role in field reconnaissance and strategic deployment. In this paper, the precise tracking algorithm of a military unmanned vehicle, based on GPS navigation, is studied. Firstly, the optimal preview point is obtained according to the data points of a differential GPS signal. Secondly, the pure tracking algorithm is used to calculate the demand steering angle, and a variable universe fuzzy sliding mode controller is designed to control the lateral motion of the vehicle, which is verified by the joint simulation platform of Simulink and CarSim, under multiple working conditions. Finally, the actual vehicle is verified by using the Autobox platform. The results show that the lateral motion control of path tracking designed in this paper can achieve an accurate and effective control effect, and has real-time performance for engineering applications. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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19 pages, 1925 KiB  
Article
Design and Control of an Omnidirectional Mobile Wall-Climbing Robot
by Zhengyu Zhong, Ming Xu, Junhao Xiao and Huimin Lu
Appl. Sci. 2021, 11(22), 11065; https://doi.org/10.3390/app112211065 - 22 Nov 2021
Cited by 11 | Viewed by 3956
Abstract
Omnidirectional mobile wall-climbing robots have better motion performance than traditional wall-climbing robots. However, there are still challenges in designing and controlling omnidirectional mobile wall-climbing robots, which can attach to non-ferromagnetic surfaces. In this paper, we design a novel wall-climbing robot, establish the robot’s [...] Read more.
Omnidirectional mobile wall-climbing robots have better motion performance than traditional wall-climbing robots. However, there are still challenges in designing and controlling omnidirectional mobile wall-climbing robots, which can attach to non-ferromagnetic surfaces. In this paper, we design a novel wall-climbing robot, establish the robot’s dynamics model, and propose a nonlinear model predictive control (NMPC)-based trajectory tracking control algorithm. Compared against state-of-the-art, the contribution is threefold: First, the combination of three-wheeled omnidirectional locomotion and non-contact negative pressure air chamber adhesion achieves omnidirectional locomotion on non-ferromagnetic vertical surfaces. Second, the critical slip state has been employed as an acceleration constraint condition, which could improve the maximum linear acceleration and the angular acceleration by 164.71% and 22.07% on average, respectively. Last, an NMPC-based trajectory tracking control algorithm is proposed. According to the simulation experiment results, the tracking accuracy is higher than the traditional PID controller. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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19 pages, 7746 KiB  
Article
Kinematic Analysis and Motion Planning of Cable-Driven Rehabilitation Robots
by Jingyu Zhang, Dianguo Cao and Yuqiang Wu
Appl. Sci. 2021, 11(21), 10441; https://doi.org/10.3390/app112110441 - 6 Nov 2021
Cited by 1 | Viewed by 2421
Abstract
In this study, a new cable-driven rehabilitation robot is designed, the overall design of the robot is given, and the kinematic equation of the lower limbs in the supine state of the human body is addressed. Considering that cable winders move along the [...] Read more.
In this study, a new cable-driven rehabilitation robot is designed, the overall design of the robot is given, and the kinematic equation of the lower limbs in the supine state of the human body is addressed. Considering that cable winders move along the rail brackets, the closed vector method is applied to establish the kinematic model of the robot, and the relationship between the human joint angle and the cable length change was deduced. Considering joint compliance, a fifth-order polynomial trajectory planning method based on an S-shaped curve is proposed by introducing an S-shaped velocity curve, and the changes in cable length displacement, velocity, and acceleration are simulated and analyzed. Three planning methods are compared based on two indices, and experimental verification is carried out on the rehabilitation experiment platform. The simulation and experimental results show that the trajectory planning method presents low energy consumption and strong flexibility, and can achieve better rehabilitation effect, which builds a good basis for the subsequent study of dynamics and control strategy. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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16 pages, 887 KiB  
Article
A Hybrid Spatial Indexing Structure of Massive Point Cloud Based on Octree and 3D R*-Tree
by Wei Wang, Yi Zhang, Genyu Ge, Qin Jiang, Yang Wang and Lihe Hu
Appl. Sci. 2021, 11(20), 9581; https://doi.org/10.3390/app11209581 - 14 Oct 2021
Cited by 5 | Viewed by 2707
Abstract
The spatial index structure is one of the most important research topics for organizing and managing massive 3D Point Cloud. As a point in Point Cloud consists of Cartesian coordinates (x,y,z), the common method to explore [...] Read more.
The spatial index structure is one of the most important research topics for organizing and managing massive 3D Point Cloud. As a point in Point Cloud consists of Cartesian coordinates (x,y,z), the common method to explore geometric information and features is nearest neighbor searching. An efficient spatial indexing structure directly affects the speed of the nearest neighbor search. Octree and kd-tree are the most used for Point Cloud data. However, octree or KD-tree do not perform best in nearest neighbor searching. A highly balanced tree, 3D R*-tree is considered the most effective method so far. So, a hybrid spatial indexing structure is proposed based on octree and 3D R*-tree. In this paper, we discussed how thresholds influence the performance of nearest neighbor searching and constructing the tree. Finally, an adaptive way method adopted to set thresholds. Furthermore, we obtained a better performance in tree construction and nearest neighbor searching than octree and 3D R*-tree. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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23 pages, 5047 KiB  
Article
Leader–Follower Role Allocation for Physical Collaboration in Human Dyads
by Rebeka Kropivšek Leskovar, Jernej Čamernik and Tadej Petrič
Appl. Sci. 2021, 11(19), 8928; https://doi.org/10.3390/app11198928 - 25 Sep 2021
Cited by 8 | Viewed by 2468
Abstract
People often find themselves in situations where collaboration with others is necessary to accomplish a particular task. In such cases, a leader–follower relationship is established to coordinate a plan to achieve a common goal. This is usually accomplished through verbal communication. However, what [...] Read more.
People often find themselves in situations where collaboration with others is necessary to accomplish a particular task. In such cases, a leader–follower relationship is established to coordinate a plan to achieve a common goal. This is usually accomplished through verbal communication. However, what happens when verbal communication is not possible? In this study, we observe the dynamics of a leader–follower relationship in human dyads during collaborative tasks where there is no verbal communication between partners. Using two robotic arms, we designed a collaborative experimental task in which subjects perform the task individually or coupled together through a virtual model. The results show that human partners fall into the leader–follower dynamics even when they cannot communicate verbally. We demonstrate this in two steps. First, we study how each subject in a collaboration influences task performance, and second, we evaluate whether both partners influence it equally or not using our proposed sorting method to objectively identify a leader. We also study the leader–follower dynamics by analysing the task performance of partners during their individual sessions to predict the role distribution in a dyad. Based on the results of our prediction method, we conclude that the higher-performing individual performance will assume the role of a leader in collaboration. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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22 pages, 31236 KiB  
Article
Risk-Sensitive Rear-Wheel Steering Control Method Based on the Risk Potential Field
by Toshinori Kojima and Pongsathorn Raksincharoensak
Appl. Sci. 2021, 11(16), 7296; https://doi.org/10.3390/app11167296 - 9 Aug 2021
Cited by 2 | Viewed by 2949
Abstract
Various driving assistance systems have been developed to reduce the number of automobile accidents. However, the control laws of these assistance systems differ based on each situation, and the discontinuous control command value may be input instantaneously. Therefore, a seamless and unified control [...] Read more.
Various driving assistance systems have been developed to reduce the number of automobile accidents. However, the control laws of these assistance systems differ based on each situation, and the discontinuous control command value may be input instantaneously. Therefore, a seamless and unified control law for driving assistance systems that can be used in multiple situations is necessary to realize more versatile autonomous driving. Although studies have been conducted on four-wheel steering that steers the rear wheels, these studies considered the role of the rear wheels only to improve vehicle dynamics and not to contribute to autonomous driving. Therefore, in this study, we define the risk potential field as a uniform control law and propose a rear-wheel steering control system that actively steers the rear wheels to contribute to autonomous driving, depending on the level of the perceived risk in the driving situation. The effectiveness of the proposed method is verified by a double lane change test, which is performed assuming emergency avoidance in simulations, and subject experiments using a driving simulator. The results indicate that actively steering the rear wheels ensures a safer and smoother drive while simultaneously improving the emergency avoidance performance. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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18 pages, 9847 KiB  
Article
The WL_PCR: A Planning for Ground-to-Pole Transition of Wheeled-Legged Pole-Climbing Robots
by Yankai Wang, Qiaoling Du, Tianhe Zhang and Chengze Xue
Robotics 2021, 10(3), 96; https://doi.org/10.3390/robotics10030096 - 27 Jul 2021
Cited by 2 | Viewed by 4494
Abstract
Hybrid mobile robots with two motion modes of a wheeled vehicle and truss structure with the ability to climb poles have significant flexibility. The motion planning of this kind of robot on a pole has been widely studied, but few studies have focused [...] Read more.
Hybrid mobile robots with two motion modes of a wheeled vehicle and truss structure with the ability to climb poles have significant flexibility. The motion planning of this kind of robot on a pole has been widely studied, but few studies have focused on the transition of the robot from the ground to the pole. In this study, a locomotion strategy of wheeled-legged pole-climbing robots (the WL_PCR) is proposed to solve the problem of ground-to-pole transition. By analyzing the force of static and dynamic process in the ground-to-pole transition, the condition of torque provided by the gripper and moving joint is proposed. The mathematical expression of Centre of Mass (CoM) of the wheeled-legged pole-climbing robots is utilized, and the conditions for the robot to smoothly transition from the ground to the vertical pole are proposed. Finally, the feasibility of this method is proved by the simulation and experimentation of a locomotion strategy on wheeled-legged pole-climbing robots. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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23 pages, 5123 KiB  
Article
Development of a Bionic Dolphin Flexible Tail Experimental Device Driven by a Steering Gear
by Bo Zhang, Qingxiang Li, Tao Wang and Zhuo Wang
Actuators 2021, 10(7), 167; https://doi.org/10.3390/act10070167 - 19 Jul 2021
Cited by 3 | Viewed by 3231
Abstract
In order to study the mechanism of the tail swing of the bionic dolphin, a flexible tail experimental device based on a steering engine was developed. This study was focused on the common three joint steering gear and its use in a bionic [...] Read more.
In order to study the mechanism of the tail swing of the bionic dolphin, a flexible tail experimental device based on a steering engine was developed. This study was focused on the common three joint steering gear and its use in a bionic dolphin tail swing mechanism, and it was found that the bionic dolphin driven by the steering gear had the problem of excessive stiffness. In order to solve this problem, we designed a bionic dolphin tail swing mechanism. The tail swing mechanism was designed rationally through the combination of a steering gear drive and two flexible spines. Analysis of kinematic and dynamic modeling was further completed. Through simulation using, the research on the bionic dolphin tail swing mechanism was verified. Experiments showed that the swing curve formed by the steering gear-driven bionic dolphin tail swing mechanism with two flexible spines fit the real fish body wave curve better than the original bionic dolphin tail swing mechanism. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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19 pages, 5338 KiB  
Article
Lane Detection Algorithm Using LRF for Autonomous Navigation of Mobile Robot
by Jong-Ho Han and Hyun-Woo Kim
Appl. Sci. 2021, 11(13), 6229; https://doi.org/10.3390/app11136229 - 5 Jul 2021
Cited by 2 | Viewed by 2836
Abstract
This paper proposes a lane detection algorithm using a laser range finder (LRF) for the autonomous navigation of a mobile robot. There are many technologies for ensuring the safety of vehicles, such as airbags, ABS, and EPS. Further, lane detection is a fundamental [...] Read more.
This paper proposes a lane detection algorithm using a laser range finder (LRF) for the autonomous navigation of a mobile robot. There are many technologies for ensuring the safety of vehicles, such as airbags, ABS, and EPS. Further, lane detection is a fundamental requirement for an automobile system that utilizes the external environment information of automobiles. Representative methods of lane recognition are vision-based and LRF-based systems. In the case of a vision-based system, the recognition of the environment of a three-dimensional space becomes excellent only in good conditions for capturing images. However, there are so many unexpected barriers, such as bad illumination, occlusions, vibrations, and thick fog, that the vision-based method cannot be used for satisfying the abovementioned fundamental requirement. In this paper, a three-dimensional lane detection algorithm using LRF that is very robust against illumination is proposed. For the three-dimensional lane detection, the laser reflection difference between the asphalt and the lane according to color and distance has been utilized with the extraction of feature points. Further, a stable tracking algorithm is introduced empirically in this research. The performance of the proposed algorithm of lane detection and tracking has been experimentally verified. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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20 pages, 1579 KiB  
Article
Model Predictive Control for Cooperative Transportation with Feasibility-Aware Policy
by Badr Elaamery, Massimo Pesavento, Teresa Aldovini, Nicola Lissandrini, Giulia Michieletto and Angelo Cenedese
Robotics 2021, 10(3), 84; https://doi.org/10.3390/robotics10030084 - 30 Jun 2021
Cited by 4 | Viewed by 5943
Abstract
The transportation of large payloads can be made possible with Multi-Robot Systems (MRS) implementing cooperative strategies. In this work, we focus on the coordinated MRS trajectory planning task exploiting a Model Predictive Control (MPC) framework addressing both the acting robots and the transported [...] Read more.
The transportation of large payloads can be made possible with Multi-Robot Systems (MRS) implementing cooperative strategies. In this work, we focus on the coordinated MRS trajectory planning task exploiting a Model Predictive Control (MPC) framework addressing both the acting robots and the transported load. In this context, the main challenge is the possible occurrence of a temporary mismatch among agents’ actions with consequent formation errors that can cause severe damage to the carried load. To mitigate this risk, the coordination scheme may leverage a leader–follower approach, in which a hierarchical strategy is in place to trade-off between the task accomplishment and the dynamics and environment constraints. Nonetheless, particularly in narrow spaces or cluttered environments, the leader’s optimal choice may lead to trajectories that are infeasible for the follower and the load. To this aim, we propose a feasibility-aware leader–follower strategy, where the leader computes a reference trajectory, and the follower accounts for its own and the load constraints; moreover, the follower is able to communicate the trajectory infeasibility to the leader, which reacts by temporarily switching to a conservative policy. The consistent MRS co-design is allowed by the MPC formulation, for both the leader and the follower: here, the prediction capability of MPC is key to guarantee a correct and efficient execution of the leader–follower coordinated action. The approach is formally stated and discussed, and a numerical campaign is conducted to validate and assess the proposed scheme, with respect to different scenarios with growing complexity. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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23 pages, 5009 KiB  
Article
Optimization of Fuzzy Logic Controller Used for a Differential Drive Wheeled Mobile Robot
by Alexandr Štefek, Van Thuan Pham, Vaclav Krivanek and Khac Lam Pham
Appl. Sci. 2021, 11(13), 6023; https://doi.org/10.3390/app11136023 - 29 Jun 2021
Cited by 36 | Viewed by 4931
Abstract
The energy-efficient motion control of a mobile robot fueled by batteries is an especially important and difficult problem, which needs to be continually addressed in order to prolong the robot’s independent operation time. Thus, in this article, a full optimization process for a [...] Read more.
The energy-efficient motion control of a mobile robot fueled by batteries is an especially important and difficult problem, which needs to be continually addressed in order to prolong the robot’s independent operation time. Thus, in this article, a full optimization process for a fuzzy logic controller (FLC) is proposed. The optimization process employs a genetic algorithm (GA) to minimize the energy consumption of a differential drive wheeled mobile robot (DDWMR) and still ensure its other performances of the motion control. The earlier approaches mainly focused on energy reduction by planning the shortest path whereas this approach aims to optimize the controller for minimizing acceleration of the robot during point-to-point movement and thus minimize the energy consumption. The proposed optimized controller is based on fuzzy logic systems. At first, an FLC has been designed based on the experiment and as well as an experience to navigate the DDWMR to a known destination by following the given path. Next, a full optimization process by using the GA is operated to automatically generate the best parameters of all membership functions for the FLC. To evaluate its effectiveness, a set of other well-known controllers have been implemented in Google Colab® and Jupyter platforms in Python language to compare them with each other. The simulation results have shown that about 110% reduction of the energy consumption was achieved using the proposed method compared to the best of six alternative controllers. Also, this simulation program has been published as an open-source code for all readers who want to continue in the research. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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13 pages, 53887 KiB  
Article
Trajectory Extrapolation for Manual Robot Remote Welding
by Lucas Christoph Ebel, Jochen Maaß, Patrick Zuther and Shahram Sheikhi
Robotics 2021, 10(2), 77; https://doi.org/10.3390/robotics10020077 - 23 May 2021
Cited by 3 | Viewed by 4678
Abstract
This article describes an algorithm for the online extrapolation of hand-motion during remote welding. The aim is to overcome the spatial limitations of the human welder’s arms in order to cover a larger workspace with a continuous weld seam and to substantially relieve [...] Read more.
This article describes an algorithm for the online extrapolation of hand-motion during remote welding. The aim is to overcome the spatial limitations of the human welder’s arms in order to cover a larger workspace with a continuous weld seam and to substantially relieve the welder from strain and fatigue. Depending on the sampled hand-motion data, an extrapolation of the given motion patterns is achieved by decomposing the input signals in a linear direction and a periodic motion component. An approach to efficiently determine the periodicity using a sampled autocorrelation function and the subsequent application of parameter identification using a spline function are presented in this paper. The proposed approach is able to resemble all practically relevant motion patterns and has been validated successfully on a remote welding system with limited input space and audio-visual feedback by an experienced welder. Full article
(This article belongs to the Topic Motion Planning and Control for Robotics)
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