Special Issue "Motion Planning and Control for Robotics"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: 31 August 2019

Special Issue Editor

Guest Editor
Dr. Marcello Bonfè

Department of Engineering – University of Ferrara, Via Saragat 1, 44122 Ferrara, Italy
Website | E-Mail
Interests: motion planning and control for robotics, design of electrical drives, automatic fault detection and isolation, formal methods for verification of logic control systems, modeling and simulation of mechatronic systems

Special Issue Information

Dear Colleagues,

Motion planning and related control issues are fundamental aspects of robotics, from both theoretical and the practical points of view. Indeed, the literature on the planning of geometric paths and the generation of time-based trajectories, taking into account the compatibility of such paths and trajectories with the kinematic and dynamic constraints of a manipulator or a mobile vehicle, is vast and full of historical references.

Nevertheless, modern robotic applications, especially those requiring one or more robot to operate in dynamic environment (e.g. human–robot collaboration and physical interaction, surveillance or exploration of unknown spaces with mobile agents, etc.), present researchers and practitioners with new and exciting challenges. In particular, planning the motion of a robot in a dynamic environment inherently implies real-time and online execution of complex computational tasks. The development of efficient solutions for such real-time computations, possibly provided by specifically designed computing architectures, optimized algorithms, and other novel contributions, is therefore a key step for the progress of modern and future-oriented robotics.

The aim of this Special Issue is to promote advancement in the following topics:

  • Collision-free robot path-planning in dynamic or unstructured environments
  • Online trajectory generation subject to kinodynamic constraints
  • Real-time systems for robotic motion-planning and control
  • Embedded control architectures for robotics
  • Reactive adaptation of robot motion-plans
  • Perception-based robot motion-control
  • Trajectory tracking with advanced control methods
  • Robot motion-control in multi-robot systems or human-robot collaborations

Dr. Marcello Bonfè
Guest Editor

Manuscript Submission Information

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Keywords

  • online kinodynamic motion planning
  • collision-free motion planning in dynamic environments
  • real-time and embedded control systems for robotics
  • trajectory tracking control algorithms for robotics
  • motion planning for human-robot collaboration
  • motion planning for reactive multi-robot systems

Published Papers (14 papers)

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Research

Open AccessArticle
Q-Learning of Straightforward Gait Pattern for Humanoid Robot Based on Automatic Training Platform
Electronics 2019, 8(6), 615; https://doi.org/10.3390/electronics8060615
Received: 12 May 2019 / Revised: 29 May 2019 / Accepted: 30 May 2019 / Published: 31 May 2019
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Abstract
In this paper, an oscillator-based gait pattern with sinusoidal functions is designed and implemented on a field-programmable gate array (FPGA) chip to generate a trajectory plan and achieve bipedal locomotion for a small-sized humanoid robot. In order to let the robot can walk [...] Read more.
In this paper, an oscillator-based gait pattern with sinusoidal functions is designed and implemented on a field-programmable gate array (FPGA) chip to generate a trajectory plan and achieve bipedal locomotion for a small-sized humanoid robot. In order to let the robot can walk straight, the turning direction is viewed as a parameter of the gait pattern and Q-learning is used to obtain a straightforward gait pattern. Moreover, an automatic training platform is designed so that the learning process is automated. In this way, the turning direction can be adjusted flexibly and efficiently under the supervision of the automatic training platform. The experimental results show that the proposed learning framework allows the humanoid robot to gradually walk straight in the automated learning process. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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Open AccessArticle
Active Disturbance Rejection Control of Multi-Joint Industrial Robots Based on Dynamic Feedforward
Electronics 2019, 8(5), 591; https://doi.org/10.3390/electronics8050591
Received: 3 May 2019 / Revised: 19 May 2019 / Accepted: 23 May 2019 / Published: 27 May 2019
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Abstract
In this paper, the dynamics-based high-performance robot motion control technology has been mainly studied, and the overall structure is controlled via dynamics forward, given the nonlinearity, strong coupling and time-variability of robots. Considering the unavailability of precise robot model parameters and the uncertain [...] Read more.
In this paper, the dynamics-based high-performance robot motion control technology has been mainly studied, and the overall structure is controlled via dynamics forward, given the nonlinearity, strong coupling and time-variability of robots. Considering the unavailability of precise robot model parameters and the uncertain disturbance in real operation, we put forward an active disturbance rejection control (ADRC) strategy based on dynamic feedforward, aiming to improve the control robustness and combining the simple structure, strong anti- disturbance ability, and no restriction from the control model of ADRC. Given the multi-joint coupling of robots, controlled decoupling is conducted by using dynamic characteristics. The ADRC cascade control structure and algorithm based on dynamic feedforward have been studied and the closed-loop stability of the system is investigated by analyzing the system dynamic linearization compensation and the anti-disturbance ability of the extended state observer. Experiments have shown the new strategy is more robust over uncertain disturbance than the conventional proportional-integral-derivative control strategy. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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Open AccessArticle
A Hierarchical Cooperative Mission Planning Mechanism for Multiple Unmanned Aerial Vehicles
Electronics 2019, 8(4), 443; https://doi.org/10.3390/electronics8040443
Received: 15 March 2019 / Revised: 7 April 2019 / Accepted: 12 April 2019 / Published: 18 April 2019
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Abstract
In this paper, the cooperative multi-task online mission planning for multiple Unmanned Aerial Vehicles (UAVs) is studied. Firstly, the dynamics of unmanned aerial vehicles and the mission planning problem are studied. Secondly, a hierarchical mechanism is proposed to deal with the complex multi-UAV [...] Read more.
In this paper, the cooperative multi-task online mission planning for multiple Unmanned Aerial Vehicles (UAVs) is studied. Firstly, the dynamics of unmanned aerial vehicles and the mission planning problem are studied. Secondly, a hierarchical mechanism is proposed to deal with the complex multi-UAV multi-task mission planning problem. In the first stage, the flight paths of UAVs are generated by the Dubins curve and B-spline mixed method, which are defined as “CBC)” curves, where “C” stands for circular arc and “B” stands for B-spline segment. In the second stage, the task assignment problem is solved as multi-base multi-traveling salesman problem, in which the “CBC” flight paths are used to estimate the trajectory costs. In the third stage, the flight trajectories of UAVs are generated by using Gaussian pseudospectral method (GPM). Thirdly, to improve the computational efficiency, the continuous and differential initial trajectories are generated based on the “CBC” flight paths. Finally, numerical simulations are presented to demonstrate the proposed approach, the designed initial solution search algorithm is compared with existing methods. These results indicate that the proposed hierarchical mission planning method can produce satisfactory mission planning results efficiently. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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Open AccessArticle
Advanced Backstepping Trajectory Control for Skid-Steered Duct-Cleaning Mobile Platforms
Electronics 2019, 8(4), 401; https://doi.org/10.3390/electronics8040401
Received: 28 January 2019 / Revised: 23 March 2019 / Accepted: 26 March 2019 / Published: 4 April 2019
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Abstract
In recent years, a novel skid-steered duct-cleaning mobile platform was developed to remove dust accumulated on the inner surface of an air-ventilation duct with its rolling brushes. During the cleaning process, the irregular brushing pressure acting on the upper arm makes it difficult [...] Read more.
In recent years, a novel skid-steered duct-cleaning mobile platform was developed to remove dust accumulated on the inner surface of an air-ventilation duct with its rolling brushes. During the cleaning process, the irregular brushing pressure acting on the upper arm makes it difficult to control the platform through the duct path. In fact, the repulsive external force due to the brushing pressure is not directly measurable or computable because of the nonlinear deformation of the brush. In addition, dynamic uncertainties in platform motion can occur during reciprocating motion of the upper arm. Therefore, a model-based trajectory-tracking controller is required to control the mobile cleaning platform by considering irregular external forces. The robustness of the developed controller based on the adaptable PD(Proportional-Derivative)-backstepping method has been proposed and evaluated through numerical analysis and experiments. For the turning motion in a narrow space, a skid-steered platform model considering wheel slippage has been also implemented. The result shows that tracking control can be successfully achieved under various conditions of frequencies in brushing-arm motion and torque limitation of the traction motors. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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Open AccessFeature PaperArticle
A Passivity-Based Strategy for Manual Corrections in Human-Robot Coaching
Electronics 2019, 8(3), 320; https://doi.org/10.3390/electronics8030320
Received: 18 February 2019 / Revised: 7 March 2019 / Accepted: 11 March 2019 / Published: 13 March 2019
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Abstract
In recent years, new programming techniques have been developed in the human-robot collaboration (HRC) field. For example, walk-through programming allows to program the robot in an easy and intuitive way. In this context, a modification of a portion of the trajectory usually requires [...] Read more.
In recent years, new programming techniques have been developed in the human-robot collaboration (HRC) field. For example, walk-through programming allows to program the robot in an easy and intuitive way. In this context, a modification of a portion of the trajectory usually requires the teaching of the path from the beginning. In this paper we propose a passivity-based method to locally change a trajectory based on a manual human correction. At the beginning the robot follows the nominal trajectory, encoded through the Dynamical Movement Primitives, by setting high control gains. When the human grasps the end-effector, the robot is made compliant and he/she can drive it along the correction. The correction is optimally joined to the nominal trajectory, resuming the path tracking. In order to avoid unstable behaviors, the variation of the control gains is performed exploiting energy tanks, preserving the passivity of the interaction. Finally, the correction is spatially fixed so that a variation in the boundary conditions (e.g., the initial/final points) does not affect the modification. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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Open AccessArticle
Network-Oriented Real-Time Embedded System Considering Synchronous Joint Space Motion for an Omnidirectional Mobile Robot
Electronics 2019, 8(3), 317; https://doi.org/10.3390/electronics8030317
Received: 8 February 2019 / Revised: 1 March 2019 / Accepted: 8 March 2019 / Published: 13 March 2019
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Abstract
This paper proposes a real-time embedded system for joint space control of omnidirectional mobile robots. Actuators driving an omnidirectional mobile robot are connected in a line topology which requires synchronization to move simultaneously in translation and rotation. We employ EtherCAT, a real-time Ethernet [...] Read more.
This paper proposes a real-time embedded system for joint space control of omnidirectional mobile robots. Actuators driving an omnidirectional mobile robot are connected in a line topology which requires synchronization to move simultaneously in translation and rotation. We employ EtherCAT, a real-time Ethernet network, to control servo controllers for the mobile robot. The first part of this study focuses on the design of a low-cost embedded system utilizing an open-source EtherCAT master. Although satisfying real-time constraints is critical, a desired trajectory on the center of the mobile robot should be decomposed into the joint space to drive the servo controllers. For the center of the robot, a convolution-based path planner and a corresponding joint space control algorithm are presented considering its physical limits. To avoid obstacles that introduce geometric constraints on the curved path, a trajectory generation algorithm considering high curvature turning points is adapted for an omnidirectional mobile robot. Tracking a high curvature path increases mathematical complexity, which requires precise synchronization between the actuators of the mobile robot. An improvement of the distributed clock—the synchronization mechanism of EtherCAT for slaves—is presented and applied to the joint controllers of the mobile robot. The local time of the EtherCAT master is dynamically adjusted according to the drift of the reference slave, which minimizes the synchronization error between each joint. Experiments are conducted on our own developed four-wheeled omnidirectional mobile robot. The experiment results confirm that the proposed system is very effective in real-time control applications for precise motion control of the robot even for tracking high curvature paths. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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Open AccessArticle
Robot Motion Planning in an Unknown Environment with Danger Space
Electronics 2019, 8(2), 201; https://doi.org/10.3390/electronics8020201
Received: 17 January 2019 / Revised: 4 February 2019 / Accepted: 7 February 2019 / Published: 10 February 2019
Cited by 3 | PDF Full-text (4703 KB) | HTML Full-text | XML Full-text
Abstract
This paper discusses the real-time optimal path planning of autonomous humanoid robots in unknown environments regarding the absence and presence of the danger space. The danger is defined as an environment which is not an obstacle nor free space and robot are permitted [...] Read more.
This paper discusses the real-time optimal path planning of autonomous humanoid robots in unknown environments regarding the absence and presence of the danger space. The danger is defined as an environment which is not an obstacle nor free space and robot are permitted to cross when no free space options are available. In other words, the danger can be defined as the potentially risky areas of the map. For example, mud pits in a wooded area and greasy floor in a factory can be considered as a danger. The synthetic potential field, linguistic method, and Markov decision processes are methods which have been reviewed for path planning in a free-danger unknown environment. The modified Markov decision processes based on the Takagi–Sugeno fuzzy inference system is implemented to reach the target in the presence and absence of the danger space. In the proposed method, the reward function has been calculated without the exact estimation of the distance and shape of the obstacles. Unlike other existing path planning algorithms, the proposed methods can work with noisy data. Additionally, the entire motion planning procedure is fully autonomous. This feature makes the robot able to work in a real situation. The discussed methods ensure the collision avoidance and convergence to the target in an optimal and safe path. An Aldebaran humanoid robot, NAO H25, has been selected to verify the presented methods. The proposed methods require only vision data which can be obtained by only one camera. The experimental results demonstrate the efficiency of the proposed methods. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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Open AccessFeature PaperArticle
A Smart Many-Core Implementation of a Motion Planning Framework along a Reference Path for Autonomous Cars
Electronics 2019, 8(2), 177; https://doi.org/10.3390/electronics8020177
Received: 26 November 2018 / Revised: 23 January 2019 / Accepted: 29 January 2019 / Published: 2 February 2019
Cited by 1 | PDF Full-text (786 KB) | HTML Full-text | XML Full-text
Abstract
Research on autonomous cars, early intensified in the 1990s, is becoming one of the main research paths in automotive industry. Recent works use Rapidly-exploring Random Trees to explore the state space along a given reference path, and to compute the minimum time collision-free [...] Read more.
Research on autonomous cars, early intensified in the 1990s, is becoming one of the main research paths in automotive industry. Recent works use Rapidly-exploring Random Trees to explore the state space along a given reference path, and to compute the minimum time collision-free path in real time. Those methods do not require good approximations of the reference path, they are able to cope with discontinuous routes, they are capable of navigating in realistic traffic scenarios, and they derive their power from an extensive computational effort directed to improve the quality of the trajectory from step to step. In this paper, we focus on re-engineering an existing state-of-the-art sequential algorithm to obtain a CUDA-based GPGPU (General Purpose Graphics Processing Units) implementation. To do that, we show how to partition the original algorithm among several working threads running on the GPU, how to propagate information among threads, and how to synchronize those threads. We also give detailed evidence on how to organize memory transfers between the CPU and the GPU (and among different CUDA kernels) such that planning times are optimized and the available memory is not exceeded while storing massive amounts of fuse data. To sum up, in our application the GPU is used for all main operations, the entire application is developed in the CUDA language, and specific attention is paid to concurrency, synchronization, and data communication. We run experiments on several real scenarios, comparing the GPU implementation with the CPU one in terms of the quality of the generated paths and in terms of computation (wall-clock) times. The results of our experiments show that embedded GPUs can be used as an enabler for real-time applications of computationally expensive planning approaches. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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Open AccessArticle
A Free Navigation of an AGV to a Non-Static Target with Obstacle Avoidance
Electronics 2019, 8(2), 159; https://doi.org/10.3390/electronics8020159
Received: 8 November 2018 / Revised: 21 January 2019 / Accepted: 23 January 2019 / Published: 1 February 2019
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Abstract
The industry is changing in order to improve the economy sector. This is the reason why technology is improving and developing new devices. The autonomous guided vehicle with free navigation is a new machine, which uses different techniques to move such as mapping, [...] Read more.
The industry is changing in order to improve the economy sector. This is the reason why technology is improving and developing new devices. The autonomous guided vehicle with free navigation is a new machine, which uses different techniques to move such as mapping, localization, path planning, and path following. In this paper, a path following is proposed. The path following is called moving to a point, which uses the proportional distance between the target and the autonomous guided vehicles (AGV) to calculate the velocity and direction. If some obstacles appear in the trajectory, however, the vehicle stops. Instead of stopping the machine, by using moving to a point logic, an obstacle avoidance function will be implemented. In this implementation, different parameters can be configured, such as: security distance, which determinates when the obstacle avoidance must correct the pose; and proportional values, which modify the velocity and steering commands. It is also compared to a dynamic window approach (DWA) obstacle avoidance solution. Additionally, the AGV navigates to a non-static target with a path following algorithm. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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Open AccessArticle
Trapezoidal Motion Profile to Suppress Residual Vibration of Flexible Object Moved by Robot
Electronics 2019, 8(1), 30; https://doi.org/10.3390/electronics8010030
Received: 16 November 2018 / Revised: 18 December 2018 / Accepted: 23 December 2018 / Published: 1 January 2019
Cited by 2 | PDF Full-text (7407 KB) | HTML Full-text | XML Full-text
Abstract
The residual vibration when a robot manipulator is operated at high speed needs to be suppressed. These vibrations are generated by the resonance of a flexible object being moved by the robot, and research on control algorithms and motion profiles is ongoing to [...] Read more.
The residual vibration when a robot manipulator is operated at high speed needs to be suppressed. These vibrations are generated by the resonance of a flexible object being moved by the robot, and research on control algorithms and motion profiles is ongoing to reduce them. In this paper, we propose a method to reduce the residual vibration of an object moved by a robot manipulator by optimizing the acceleration/deceleration time calculated using the object’s natural frequency. The relationship between acceleration/deceleration time and the residual vibration in a trapezoidal velocity profile is considered by analyzing the scenario when the jerking motion characteristic of such vibrations occurs. The results of experiments using a commercial robot show that residual vibrations can be reduced by the proposed method without the need for an additional feedback control algorithm while transferring a flexible object over small and large distances. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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Open AccessArticle
Learning the Metric of Task Constraint Manifolds for Constrained Motion Planning
Electronics 2018, 7(12), 395; https://doi.org/10.3390/electronics7120395
Received: 11 September 2018 / Revised: 26 November 2018 / Accepted: 3 December 2018 / Published: 5 December 2018
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Abstract
Finding feasible motion for robots with high-dimensional configuration space is a fundamental problem in robotics. Sampling-based motion planning algorithms have been shown to be effective for these high-dimensional systems. However, robots are often subject to task constraints (e.g., keeping a glass of water [...] Read more.
Finding feasible motion for robots with high-dimensional configuration space is a fundamental problem in robotics. Sampling-based motion planning algorithms have been shown to be effective for these high-dimensional systems. However, robots are often subject to task constraints (e.g., keeping a glass of water upright, opening doors and coordinating operation with dual manipulators), which introduce significant challenges to sampling-based motion planners. In this work, we introduce a method to establish approximate model for constraint manifolds, and to compute an approximate metric for constraint manifolds. The manifold metric is combined with motion planning methods based on projection operations, which greatly improves the efficiency and success rate of motion planning tasks under constraints. The proposed method Approximate Graph-based Constrained Bi-direction Rapidly Exploring Tree (AG-CBiRRT), which improves upon CBiRRT, and CBiRRT were tested on several task constraints, highlighting the benefits of our approach for constrained motion planning tasks. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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Open AccessArticle
A Fast Global Flight Path Planning Algorithm Based on Space Circumscription and Sparse Visibility Graph for Unmanned Aerial Vehicle
Electronics 2018, 7(12), 375; https://doi.org/10.3390/electronics7120375
Received: 30 September 2018 / Revised: 14 November 2018 / Accepted: 27 November 2018 / Published: 2 December 2018
Cited by 1 | PDF Full-text (1297 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a new flight path planning algorithm that finds collision-free, optimal/near-optimal and flyable paths for unmanned aerial vehicles (UAVs) in three-dimensional (3D) environments with fixed obstacles. The proposed algorithm significantly reduces pathfinding computing time without significantly degrading path lengths by using [...] Read more.
This paper proposes a new flight path planning algorithm that finds collision-free, optimal/near-optimal and flyable paths for unmanned aerial vehicles (UAVs) in three-dimensional (3D) environments with fixed obstacles. The proposed algorithm significantly reduces pathfinding computing time without significantly degrading path lengths by using space circumscription and a sparse visibility graph in the pathfinding process. We devise a novel method by exploiting the information about obstacle geometry to circumscribe the search space in the form of a half cylinder from which a working path for UAV can be computed without sacrificing the guarantees on near-optimality and speed. Furthermore, we generate a sparse visibility graph from the circumscribed space and find the initial path, which is subsequently optimized. The proposed algorithm effectively resolves the efficiency and optimality trade-off by searching the path only from the high priority circumscribed space of a map. The simulation results obtained from various maps, and comparison with the existing methods show the effectiveness of the proposed algorithm and verify the aforementioned claims. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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Open AccessArticle
Complete Path Planning for a Tetris-Inspired Self-Reconfigurable Robot by the Genetic Algorithm of the Traveling Salesman Problem
Electronics 2018, 7(12), 344; https://doi.org/10.3390/electronics7120344
Received: 8 October 2018 / Revised: 31 October 2018 / Accepted: 12 November 2018 / Published: 22 November 2018
Cited by 2 | PDF Full-text (3054 KB) | HTML Full-text | XML Full-text
Abstract
The efficiency of autonomous systems that tackle tasks such as home cleaning, agriculture harvesting, and mineral mining depends heavily on the adopted area coverage strategy. Extensive navigation strategies have been studied and developed, but few focus on scenarios with reconfigurable robot agents. This [...] Read more.
The efficiency of autonomous systems that tackle tasks such as home cleaning, agriculture harvesting, and mineral mining depends heavily on the adopted area coverage strategy. Extensive navigation strategies have been studied and developed, but few focus on scenarios with reconfigurable robot agents. This paper proposes a navigation strategy that accomplishes complete path planning for a Tetris-inspired hinge-based self-reconfigurable robot (hTetro), which consists of two main phases. In the first phase, polyomino form-based tilesets are generated to cover the predefined area based on the tiling theory, which generates a series of unsequenced waypoints that guarantee complete coverage of the entire workspace. Each waypoint specifies the position of the robot and the robot morphology on the map. In the second phase, an energy consumption evaluation model is constructed in order to determine a valid strategy to generate the sequence of the waypoints. The cost value between waypoints is formulated under the consideration of the hTetro robot platform’s kinematic design, where we calculate the minimum sum of displacement of the four blocks in the hTetro robot. With the cost function determined, the waypoint sequencing problem is then formulated as a travelling salesman problem (TSP). In this paper, a genetic algorithm (GA) is proposed as a strong candidate to solve the TSP. The GA produces a viable navigation sequence for the hTetro robot to follow and to accomplish complete coverage tasks. We performed an analysis across several complete coverage algorithms including zigzag, spiral, and greedy search to demonstrate that TSP with GA is a valid and considerably consistent waypoint sequencing strategy that can be implemented in real-world hTetro robot navigations. The scalability of the proposed framework allows the algorithm to produce reliable results while navigating within larger workspaces in the real world, and the flexibility of the framework ensures easy implementation of the algorithm on other polynomial-based shape shifting robots. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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Open AccessArticle
Path Planning for Mobile Agents Using a Genetic Algorithm with a Direction Guided Factor
Electronics 2018, 7(10), 212; https://doi.org/10.3390/electronics7100212
Received: 11 August 2018 / Revised: 16 September 2018 / Accepted: 20 September 2018 / Published: 22 September 2018
Cited by 3 | PDF Full-text (39719 KB) | HTML Full-text | XML Full-text
Abstract
This paper suggests a novel methodology in collision-free shortest path planning (CFSPP) problems for mobile agents (MAs) using a method that combines a genetic algorithm (GA) and a direction factor toward a target point. In the CFSPP problem, MAs find the shortest path [...] Read more.
This paper suggests a novel methodology in collision-free shortest path planning (CFSPP) problems for mobile agents (MAs) using a method that combines a genetic algorithm (GA) and a direction factor toward a target point. In the CFSPP problem, MAs find the shortest path from the starting point to the target point while avoiding certain obstacles. The paper proposes an obstacle-based search methodology that identifies critical collision-free points adjacent to given obstacles. When critical obstacles are found via CFSPP, this study suggests favorable paths in 2-dimensional space found using the obstacle-based GA (OBGA). The OBGA has four advantages. First, it effectively narrows the search spaces compared to free space-based methodologies. It also determines shorter collision-free paths, and it only requires a short amount of time. Finally, convergence occurs more quickly than in previous studies. The proposed method also works properly in larger and more complex environments, indicating that it can be applied to more practical problems. Full article
(This article belongs to the Special Issue Motion Planning and Control for Robotics)
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