Author(s)

Guanghong Liang ¹, Weigang Yan ¹, Yongxiang Fan ¹

Affiliation(s)

¹ School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai, China

Corresponding Author

Guanghong Liang

ABSTRACT

In multi-vehicle formation scenarios, obstacle avoidance in unknown environments presents several challenges, such as obstacles near the target, entrapment in local minima, and dynamic obstacle interference. To address these issues in multi-vehicle formation control, this paper proposes an optimization algorithm that enhances the artificial potential field (APF) method with PID control. Simulation experiments demonstrate that, compared to benchmark algorithms, the proposed method achieves reductions of 32.4%, 41.9%, 24.8%, and 32.0% in the number of total iterations, formation efficiency function value, energy consumption, and iteration standard deviation, respectively. The improved approach effectively resolves slow obstacle avoidance near the target, overcomes local minima issues, handles dynamic obstacles, exhibits enhanced robustness, and realizes energy-efficient obstacle avoidance in complex environments.

KEYWORDS

PID Control; Multi-Vehicle Systems; Formation Obstacle Avoidance; Leader–Follower Method; Artificial Potential Field; Energy Efficiency

CITE THIS PAPER

Guanghong Liang, Weigang Yan, Yongxiang Fan, Energy-Efficient Obstacle Avoidance Optimization for Multi-Vehicle Systems Based on an Improved Artificial Potential Field with PID Control. Automation and Machine Learning (2025) Vol. 6: 135-145. DOI: http://dx.doi.org/10.23977/autml.2025.060116.

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