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Improving the Lifelong Planning A-star algorithm to satisfy path planning for space truss cellular robots with dynamic obstacles

Published online by Cambridge University Press:  24 February 2025

Ye Dai Open the ORCID record for Ye Dai [Opens in a new window] ,
Weijian Lv ,
Shikun Li  and
Muyan Zong
Ye Dai*
Affiliation:
Key Laboratory of Advanced Manufacturing Intelligent Technology of Ministry of Education, Harbin University of Science and Technology, Harbin, China
Weijian Lv
Affiliation:
Key Laboratory of Advanced Manufacturing Intelligent Technology of Ministry of Education, Harbin University of Science and Technology, Harbin, China
Shikun Li
Affiliation:
Key Laboratory of Advanced Manufacturing Intelligent Technology of Ministry of Education, Harbin University of Science and Technology, Harbin, China
Muyan Zong
Affiliation:
Key Laboratory of Advanced Manufacturing Intelligent Technology of Ministry of Education, Harbin University of Science and Technology, Harbin, China
*
Corresponding author: Ye Dai; Email: [email protected]
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Abstract

In this paper, a cellular robot for space trusses is structured so that it can perform tasks such as moving the truss and assembling the truss. There may be some spatial operating mechanisms on the space truss that cause obstacles to the robot’s movement, especially other mobile mechanical devices that are working, which are dynamic obstacles, so a suitable path planning for the robot is needed. In path planning, A-star algorithm has the advantages of efficient searching speed and good optimization effect, but it can’t deal with the path planning problem with dynamic obstacles, so this paper improves Lifelong Planning A-star (LPA-star) algorithm so that the improved algorithm satisfies the dynamic path planning task. Then a three-dimensional truss mathematical model is established, a dynamic obstacle environment is set up, the improved LPA-star algorithm is used for path planning, and the unimproved LPA-star algorithm and the improved A-star algorithm are used to compare with it. The simulation results show that in the environment set up in this paper, the optimal path length of the improved LPA-star algorithm is shortened by about 25% and the algorithm search time is shortened by about 55% compared with the improved A-star algorithm; while the unimproved LPA-star algorithm is unable to accomplish the dynamic path planning task. Therefore, the improved LPA-star algorithm can reduce the robot’s moving distance and time consumption.

Keywords

cellular robotsspace trussstructure designimproved Lifelong Planning A-star algorithmpath planning
Type
Research Article
Information
Robotica , First View , pp. 1 - 15
Copyright
© The Author(s), 2025. Published by Cambridge University Press

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