The Research on the Improved A Combined with DWA for Robot Path Planning Algorithm

In the power system, substations play a crucial role in tasks such as voltage transformation and power distribution. To ensure their safe operation, substation inspection robots can be utilized to guarantee the healthy operation of substation equipment. This requires the robot to possess a certain l...

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Bibliographic Details
Published in:2025 International Conference of Clean Energy and Electrical Engineering (ICCEEE) pp. 1 - 8
Main Authors: Nan, Chen, Zihan, Hao, Lihui, Gao, Jialin, Cai, Binbin, Chen, Xuan, Zhang, Jinxin, Li, Shijin, Li
Format: Conference Proceeding
Language:English
Published: IEEE 18.07.2025
Subjects:
A algorithm
Collision avoidance
DWA algorithm (key words)
Heuristic algorithms
Inspection
Jump point search
Path planning
Planning
Power distribution
Search problems
Substations
Turning
Voltage
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Summary:In the power system, substations play a crucial role in tasks such as voltage transformation and power distribution. To ensure their safe operation, substation inspection robots can be utilized to guarantee the healthy operation of substation equipment. This requires the robot to possess a certain level of autonomous navigation and path planning capabilities.In response to the issues of long planning time, a large number of turning points and non-smooth path in the original A^{*} algorithm. Based on the original A^{*}, the search strategy is optimized by integrating the jump point algorithm, and the heuristic function is enhanced. At the same time, improve smoothness and search efficiency, and reduce the number of turning points. Finally, a smooth path is achieved. Experimental results demonstrate that, in comparison with the original A^{*} algorithm, the improved A^{*} algorithm proposed in this paper outperforms it in terms of running time, path length, and the number of path turning points, and the planned path is smoother. Regarding the issue that the A^{*} algorithm encounters difficulties in avoiding unknown obstacles in complex environments, the improved A* algorithm is integrated with the improved DWA(Dynamic Window Approach) algorithm to develop a hybrid path planning method. Experimental results demonstrate that this hybrid planning method can conduct local obstacle avoidance while guaranteeing global optimality. ()
DOI:10.1109/ICCEEE63357.2025.11156925