Towards the Achievement of Path Planning with Multi-robot Systems in Dynamic Environments

Kyprianou, Georgios; Doitsidis, Lefteris; Chatzichristofis, Savvas A.

doi:10.1007/s10846-021-01555-3

Cited by 17 publications

(4 citation statements)

References 92 publications

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“…It can function effectively without prior knowledge of the workspace, making it versatile and adaptable to various scenarios and changing environments. In contrast, several other approaches often rely on prior knowledge of the workspace, limiting their adaptability to dynamic settings [40], [13], [58], [66], [71], [77]. Complete and non-repetitive coverage is a key focus of the proposed algorithm, ensuring that all areas are covered without unnecessary revisits to already explored regions.…”

Section: Resultsmentioning

confidence: 99%

“…In [65], a complete hybrid navigation system for a class of mobile robots with load tasks and docking tasks is presented. The challenges and potential solutions for path planning in Multiple Robotic Systems (MRS) are surveyed, emphasizing the need for more research and practical applications in dynamic environments is presented in [66]. An algorithm based on neural dynamics is proposed to achieve complete coverage of a grid-based environment while considering collision avoidance and dead-end situations for mobile robots, demonstrating improvements in collision-free effective path planning in [67].…”

Section: Journal Ofmentioning

confidence: 99%

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Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

Nair

2024

Journal of Robotics and Control

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In this paper, we introduce an efficient path planning algorithm designed for floor cleaning applications, utilizing the concept of Spanning Tree Coverage (STC). We operate under the assumption that the environment, i.e., the floor, is initially unknown to the robot, which also lacks knowledge regarding obstacle positions, except for the workspace boundaries. The robot executes alternating phases of exploration and coverage, leveraging the local map generated during exploration to construct a STC tree, which then guides the subsequent coverage (cleaning) phase. The extent of exploration is determined by the range of the robot's sensors. The path generation algorithms for cleaning fall within the broader category of coverage path planning (CPP) algorithms. A key advantage of this algorithm is that the robot returns to its initial position upon completing the operation, minimizing battery usage since sensors are only active during the exploration phase. We classify the proposed algorithm as an offline-online scheme. To validate the effectiveness and non-repetitive nature of the algorithm, we conducted simulations using VRep/MATLAB environments and implemented real-time experiments using Turtlebot in the ROS-Gazebo environment. The results substantiate the completeness of coverage and underscore the algorithm's significance in applications akin to floor cleaning.

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Section: Resultsmentioning

confidence: 99%

Section: Journal Ofmentioning

confidence: 99%

Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

Nair

2024

Journal of Robotics and Control

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“…However, high automation puts forward higher performance requirements for manipulator motion planning, and shorter time and shorter path have gradually become the goal of manipulator motion planning. The current mainstream algorithm for manipulator trajectory planning is the RRT algorithm, because the RRT algorithm can realize path search in high-dimensional space [2].…”

Section: Introductionmentioning

confidence: 99%

Manipulator Motion Planning Based on Improved RRT Algorithm

Song

Li²,

Pu³

2023

J. Phys.: Conf. Ser.

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Aiming at the problems that the Rapidly-exploring Random Tree (RRT) algorithm has more time-consuming and longer paths in the manipulator motion planning, we propose an improved RRT algorithm based on probabilistic target bias strategy and triangular inequality pruning method. This paper simulates the algorithm from three dynamic environments with different numbers of obstacles. The simulation results show that the proposed improved RRT algorithm can plan a shorter path in less time.

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“…Similarly, the genetic algorithm (GA) has established itself as an effective optimization tool for path planning. Studies have shown its effectiveness in environments with stationary and mobile obstacles [12]. Although the above-mentioned strategy has a wide search range, rapid search speed, and high computational efficiency, the high calculation cost and slow convergence speed are two intractable shortcomings.…”

Section: Introductionmentioning

confidence: 99%

Dual-Quaternion-Based SLERP MPC Local Controller for Safe Self-Driving of Robotic Wheelchairs

Wang,

Cao,

Takanishi

2023

Robotics

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In this work, the motion control of a robotic wheelchair to achieve safe and intelligent movement in an unknown scenario is proposed. The primary objective is to develop a comprehensive framework for a robotic wheelchair that combines a global path planner and a model predictive control (MPC) local controller. The A* algorithm is employed to generate a global path. To ensure safe and directional motion for the wheelchair user, an MPC local controller is implemented taking into account the via points generated by an approach combined with dual quaternions and spherical linear interpolation (SLERP). Dual quaternions are utilized for their simultaneous handling of rotation and translation, while SLERP enables smooth and continuous rotation interpolation by generating intermediate orientations between two specified orientations. The integration of these two methods optimizes navigation performance. The system is built on the Robot Operating System (ROS), with an electric wheelchair equipped with 3D-LiDAR serving as the hardware foundation. The experimental results reveal the effectiveness of the proposed method and demonstrate the ability of the robotic wheelchair to move safely from the initial position to the destination. This work contributes to the development of effective motion control for robotic wheelchairs, focusing on safety and improving the user experience when navigating in unknown environments.

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Towards the Achievement of Path Planning with Multi-robot Systems in Dynamic Environments

Cited by 17 publications

References 92 publications

Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

Manipulator Motion Planning Based on Improved RRT Algorithm

Dual-Quaternion-Based SLERP MPC Local Controller for Safe Self-Driving of Robotic Wheelchairs

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