Title: Intelligent robot obstacle avoidance decision based on dynamic extended neighbourhood ant colony algorithm

Authors: Zhihong Qin; Fumin Shang; Fuhong Geng

Addresses: Department of Network Security, Henan Police College, Zhengzhou, Henan, 450046, China ' International Education College, Zhengzhou University of Light Industry, Zhengzhou, 450001, China ' Automation major of School of Electrical Engineering, Xinjiang University, Wulumuqi, 830046, China

Abstract: In order to overcome the problems of low path smoothness, low decision accuracy, and long response time in traditional intelligent robot obstacle avoidance decision-making methods, an intelligent robot obstacle avoidance decision method based on dynamic extended neighbourhood ant colony algorithm is proposed. Collect environmental data of intelligent robots through structured light depth camera, perform voxel filtering on the collected data, and build a grid map based on the collected data. In a grid map, the dynamic extended neighbourhood ant colony algorithm finds the optimal obstacle avoidance path for intelligent robots through optimisation, thereby achieving intelligent robot obstacle avoidance decision-making. The experimental results show that the average smoothness of the obstacle avoidance path of the proposed method for intelligent robots is 9.63, the decision accuracy is always above 90.68%, and the average response time is 139.66ms. The intelligent robot has a good obstacle avoidance effect.

Keywords: dynamic extended neighbourhood ant colony algorithm; intelligent robot; obstacle avoidance decision-making; structured light depth camera; Voxel filtering.

DOI: 10.1504/IJSCC.2026.155211

International Journal of Systems, Control and Communications, 2026 Vol.17 No.3, pp.327 - 346

Received: 24 Mar 2025
Accepted: 16 Jun 2025
Published online: 29 Jul 2026 *

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