Title: An adaptive collaborative control method for multiple mobile robots based on improved genetic algorithm

Authors: Yuanquan Zhong; Shaowei Zhang

Addresses: Department of Computer Engineering, Anhui Wenda University of Information Engineering, Hefei, 231201, China ' Department of Computer Engineering, Anhui Wenda University of Information Engineering, Hefei, 231201, China

Abstract: To diminish the positional control inaccuracies of robots and elevate the success rate of collision evasion among them, a novel adaptive collaborative control approach utilising an enhanced genetic algorithm for multiple mobile robots has been introduced. Initially, within the confines of a rotational angle, an adaptive collaborative control objective function is formulated to facilitate collision avoidance, integrating the variable step size of movement. Subsequently, to bolster the convergence efficiency of the genetic algorithm, the introduction of hypothetical tasks serves to refine the algorithm's performance. Ultimately, the fitness function of the refined genetic algorithm is computed, the objective function is resolved using this fitness metric, yielding the optimal solution, thereby achieving the adaptive collaborative control for multiple mobile robots. Empirical findings indicate a marked reduction in positional control discrepancies, with a minimum deviation of merely 0.13 metres, and a substantial enhancement in collision avoidance success, consistently exceeding 95%.

Keywords: improved genetic algorithm; multiple mobile robots; adaptive collaborative control; rotation angle.

DOI: 10.1504/IJMIC.2024.144031

International Journal of Modelling, Identification and Control, 2024 Vol.45 No.4, pp.225 - 231

Received: 22 Dec 2023
Accepted: 19 Jun 2024
Published online: 21 Jan 2025 *

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