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
  • [1] SALONI W., The role of autonomous unmanned ground vehicle technologies in defense application, (2020)
  • [2] LEONARDB, TOMA, HENNINGS, State of the art-automated micro-vehicles for urban logistics[J], International Federation of Automatic Control, 52, 13, pp. 2455-2462, (2019)
  • [3] SANTOS L C, SANTOS F N, PIRES E J S, Et al., Path planning for ground robots in agriculture: a short review, Proc. of the IEEE International Conference on Autonomous Robot Systems and Competitions, pp. 61-66, (2020)
  • [4] ALGIRDASV V, OLEGASC, VADIMV, Motion and energy efficiency parameters of the unmanned ground vehicle, Solid State Phenomena, 220, pp. 934-939, (2015)
  • [5] DIK C, LIUZ Q, WANW H, Et al., Geospatial technologies for Chang'e-3 and Chang'e-4 lunar rover missions[J], Geo-spatial Information Science, 23, 1, pp. 87-97, (2020)
  • [6] 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)
  • [7] RAPPAPORT M., Energy-aware mobile robot exploration with adaptive decision thresholds, Proc. of the 47th International Symposium on Robotics, pp. 236-243, (2016)
  • [8] VALIAOTSE, SELLR, Energy efficiency profiles for unmanned ground vehicles[J], Proceedings of the Estonian Academy of Sciences, 68, 1, pp. 55-65, (2019)
  • [9] SHARIF A, LAHIRU H M, HERATH S, Et al., Energy efficient path planning of hybrid fly-drive robot using A* algorithm, Proc. of the 15th International Conference on Informatics in Control, Automation and Robotics, pp. 201-210, (2018)
  • [10] HILL R B., Design of high-speed robots with drastically reduced energy consumption, (2019)