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A Real-time Path Planning Algorithm for Mobile Robots Based on Safety Distance Matrix and Adaptive Weight Adjustment Strategy

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  • Robot and Applications
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Abstract

The fusion of the A* and the dynamic windowing algorithm is commonly used for the path planning of mobile robots in dynamic environments. However, the planned path has the problems of redundancy and low security. This paper proposes a path planning algorithm based on the safety distance matrix and adaptive weight adjustment strategy to address the above problems. Firstly, the safety distance matrix and new heuristic function are added to the traditional A* algorithm to improve the safety of global path. Secondly, the weight of the evaluation sub-function in the dynamic window algorithm is adjusted through an adaptive weight adjustment strategy to solve the problem of path redundancy. Then, the above two improved algorithms are fused to make the mobile robot have dynamic obstacle avoidance capability by constructing a new global path evaluation function. Finally, simulations are performed on grid maps, and the fusion algorithm is applied to the actual mobile robot path planning based on the ROS. Simulation and experimental results show that the fusion algorithm achieves optimization of path safety and length, enabling the robot to reach the end point safely with real-time dynamic obstacle avoidance capability.

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Authors and Affiliations

  1. College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan, 030024, China

    Xinpeng Zhai, Jianyan Tian & Jifu Li

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  1. Xinpeng Zhai
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  2. Jianyan Tian
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  3. Jifu Li
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Correspondence to Jianyan Tian.

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The authors declare that there is no competing financial interest or personal relationship that could have appeared to influence the work reported in this paper.

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This work was supported by the Nature Scinece Foundation of Shanxi Province of China under Grant (201901D111092) and Key Research and Development (R&D) Projects (Intelligent Field) of Shanxi Province of China (2021_6)

Xinpeng Zhai received his B.S. degree from School of Electrical Engineering and Automation, Qilu University of Technology, in 2017, and an M.S. degree from Institute of Automation, Shandong Academy of Sciences, in 2020. He is currently pursuing a Ph.D. degree in College of Electrical and Power Engineering, Taiyuan University of Technology. His current research interests include image processing and intelligent robot control.

Jianyan Tian received her B.S. and M.S. degrees in control science and engineering from College of Electrical and Power Engineering, Taiyuan University of Technology, in 1988 and 1993, respectively. She received a Ph.D. degree in system engineering from Nanjing University of Aeronautics and Astronautics, in 2008. She is a Professor at College of Electrical and Power Engineering, Taiyuan University of Technology. Her research interests include modeling of complex systems, intelligent control systems, and intelligent robot.

Jifu Li received his B.S. degree in automation from Beijing Institute of Technology, in 2017, and an M.S. degree in electrical engineering from Texas A&M Univrsity, College Station, in 2019. He is currently working toward a Ph.D. degree in electrical engineering at Taiyuan University of Technology. His current research interests include robotics, machine vision, and GIS partial discharge detection.

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Zhai, X., Tian, J. & Li, J. A Real-time Path Planning Algorithm for Mobile Robots Based on Safety Distance Matrix and Adaptive Weight Adjustment Strategy. Int. J. Control Autom. Syst. 22, 1385–1399 (2024). https://doi.org/10.1007/s12555-022-1016-5

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  • DOI: https://doi.org/10.1007/s12555-022-1016-5

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