Abstract
Given a large amount of calculation in the traditional path planning algorithm and the inability to control the distance between the path and the obstacle, a path planning method based on a regional index is proposed in this paper. First, by comparing the three methods of measuring distance, the characteristics of the regional index method are outlined, and how to divide regions and the corresponding regional indicators are outlined. Secondly, the potential energy distribution maps by use of the traditional method and the regional index method respectively are analyzed, and the regional indicators method can be used to plan the path artificially. Finally, through simulation, four paths are obtained applying two artificial potential field methods and two regional index methods. By comparing the characteristics of these four paths, it is found that the regional index method can guarantee the distance between the path and the obstacle very well, which verifies the effectiveness of the method.
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References
Chen, Y., Bai, G., Zhan, Y., Hu, X., Liu, J.: Path planning and obstacle avoiding of the USV based on improved ACO-APF hybrid algorithm with adaptive early-warning. IEEE Access 9, 40728–40742 (2021)
Lu, Y., Tang, K., Wang, C.: Collision-free and smooth joint motion planning for six-axis industrial robots by redundancy optimization. Robot. Comput. Integrated Manuf. 68, 1–16 (2021)
Sang, H., You, Y., Sun, X., Zhou, Y., Liu, F.: The hybrid path planning algorithm based on improved A* and artificial potential field for unmanned surface vehicle formations. Ocean Eng. 223, 1–16 (2021)
Zhao, Y., Liu, J., Ma, J., Wu, L.: Multi-branch cable harness layout design based on genetic algorithm with probabilistic roadmap method. Chinese J. Mech. Eng. 34(1), 1–11 (2021)
Ravankar, A., Ravankar, A., Emaru, T., Kobayashi, Y.: HPPRM: Hybrid potential based probabilistic roadmap algorithm for improved dynamic path planning of mobile robots. IEEE Access 8, 221743–221766 (2020)
Wang, J., Li, B., Meng, M.: Kinematic constrained bi-directional RRT with efficient branch pruning for robot path planning. Expert Syst. Appl. 170, 1–7 (2021)
Yu, Z., Xiang, L.: NPQ-RRT*: an improved RRT* approach to hybrid path planning. Complexity 2021, 1–10 (2021)
Milad, N., Esmaeel, K., Samira, D.: Multi-objective multi-robot path planning in continuous environment using an enhanced genetic algorithm. Expert Syst. Appl. 115, 106–120 (2019)
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Jia, L., Guo, Y., Tao, Y., Cai, H., Fu, T., Huang, Y. (2021). A Novel Path Planning Method Based on Regional Index Algorithm for Hyper-redundant Manipulator. In: Liu, XJ., Nie, Z., Yu, J., Xie, F., Song, R. (eds) Intelligent Robotics and Applications. ICIRA 2021. Lecture Notes in Computer Science(), vol 13016. Springer, Cham. https://doi.org/10.1007/978-3-030-89092-6_61
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DOI: https://doi.org/10.1007/978-3-030-89092-6_61
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