Energy-efficient path planning method for robots based on improved A* algorithm

被引:2
作者
Zhang H. [1 ]
Zhang Y. [1 ]
Liang R. [1 ]
Yang T. [2 ]
机构
[1] Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing
[2] Weapon Technology Innovation Center, Ordnance Science and Research Academy of China, Beijing
来源
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2023年 / 45卷 / 02期
关键词
energy consumption model; energy consumption motion primitive; improved A* algorithm; path planning;
D O I
10.12305/j.issn.1001-506X.2023.02.23
中图分类号
学科分类号
摘要
In order to reduce the energy consumption during the robot movements and increase the task execution rate with limit energy supply, an energy-efficient path planning method is proposed based on improved A* algorithm for mobile robots. Firstly, the energy consumption model of four-wheel differential drive robot is established according to its kinematic constraints. Secondly, the motion primitive of the robot is solved by given the start and goal states. The energy consumption motion primitive set is constructed after using the energy consumption model to calculate the cost of each motion primitive. Thirdly, the energy efficient path planning method is proposed based on the traditional A* algorithm. In the planning process, the nodes are expanded using the defined connection relationship in energy consumption motion primitive set and the energy consumption is treated as the cost between them, which guarantees to find a global energy efficient path. Finally, the offline map simulation test and robotic experiment results show that the energy cost of the generated path is reduced by about 28.24%. Therefore, the effectiveness of the algorithm is verified. © 2023 Chinese Institute of Electronics. All rights reserved.
引用
收藏
页码:513 / 520
页数:7
相关论文
共 35 条
  • [11] ROWEN C, ROSSR S., Optimal grid-free path planning across arbitrarily contoured terrain with anisotropic friction and gravity effects, IEEE Trans.on Robotics and Automation, 6, 5, pp. 540-553, (1990)
  • [12] ZHANGH J, ZHANGY D, YANGT T., A survey of energy-efficient motion planning for wheeled mobile robots[J], Industrial Robot: the International Journal of Robotics Research and Application, 4, 47, pp. 607-621, (2020)
  • [13] SUNZ, REIFJ H., On finding energy-minimizing paths on terrains[J], IEEE Trans.on Robotics, 21, 1, pp. 102-114, (2005)
  • [14] SAAD M, SALAMEH A I, ABDALLAH S., Energy-efficient shortest path planning on uneven terrains: a composite routing metric approach, Proc. of the 19th International Symposium on Signal Processing and Information Technology, (2019)
  • [15] SAADM, SALAMEHA I, ABDALLAHS, Et al., A compo-site metric routing approach for energy-efficient shortest path planning on natural terrains[J], Applied Sciences, 11, 15, (2021)
  • [16] YINJ J, DONGW L, LIANGL H, Et al., Optimization method of agricultural robot path planning in complex environment[J], Transactions of the Chinese Society for Agricultural Machinery, 50, 5, pp. 17-22, (2019)
  • [17] ZAKHAROV K, SAVELIEV A, SIVCHENKO O., Energy-efficient path planning algorithm on three-dimensional large-scale terrain maps for mobile robots, Proc. of the 5th International Conference on Interactive Collaborative Robotics, pp. 319-330, (2020)
  • [18] ZHANGZ W, WUL H, ZHANGW Q, Et al., Energy-efficient path planning for a single-load automated guided vehicle in a manufacturing workshop, Computers & Industrial Engineering, 158, (2021)
  • [19] ZHANGX L, HUANGY, RONGY M, Et al., Optimal trajectory planning for wheeled mobile robots under localization uncertainty and energy efficiency constraints[J], Sensors, 21, 2, (2021)
  • [20] SANGEETHAV, KRISHANKUMARR, RAVICHANDRANK S, Et al., Energy-efficient green ant colony optimization for path planning in dynamic 3D environments, Soft Computing, 25, pp. 4749-4769, (2021)