Multi-point test path planning based on improved A-star and grey wolf algorithms
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School of Mechanical Engineering, Donghua University,Shanghai 201600, China

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TN98;TP29

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    Abstract:

    Aiming at the multi-point path planning problem for electromagnetic interference testing, a path planning method based on the combination of improved A-star algorithm and grey wolf optimization algorithm is proposed. First, the traditional A-start algorithm is improved by modifying the heuristic function and introducing a redundant point deletion strategy, thereby reducing path length and algorithm runtime. Then, the test path planning problem is transformed into a classic traveling salesman problem and solved using the improved gray wolf optimization algorithm to obtain the optimal test path. Experimental results demonstrate that compared to traditional methods, the improved approach achieves an average reduction of 4.73% in total path planning distance, 30.42% in average number of turns, 34.74% in average total turning angle, and 39.47% in average computation time. This effectively enhances testing efficiency and safety, providing a reliable solution for electromagnetic interference multi-target point testing tasks.

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  • Received:
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  • Online: April 16,2026
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