首页|Enhancing Stability of Multi-Underwater Robot Swarms Based on the Fusion of Social Force and Vicsek Models
Enhancing Stability of Multi-Underwater Robot Swarms Based on the Fusion of Social Force and Vicsek Models
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NETL
NSTL
World Scientific
As the demand for marine environmental monitoring and deep-sea operations continues to grow, AUV swarm systems have become a research hotspot due to their high flexibility. This paper proposes a navigation control method for multi-AUV swarms that integrates the Social Force Model (SFM) with the Vicsek model to improve collaboration efficiency and motion stability in dynamic underwater environments. The proposed control strategy incorporates both physical forces and alignment mechanisms to achieve dynamic behavioral coordination among the robots in the swarm. The SFM is used to characterize interactions between individuals, ensuring collision avoidance, while the Vicsek model provides a neighborhood-based velocity alignment mechanism to enhance swarm coherence. Additionally, the control framework introduces a leader-follower structure, effectively integrating local perception with global navigation information. Simulation results indicate that the robot swarm can maintain effective obstacle avoidance and structural stability even in complex environments with obstacles. In the absence of the Vicsek model, navigation tasks may fail or significantly increase navigation time. Even with low alignment strength and higher speeds, navigation time can be reduced by 35%, while higher alignment strength combined with lower speeds can shorten navigation time by up to 50%. Tests with large-scale swarms demonstrate that the proposed method exhibits good scalability and effectively prevents excessive aggregation within the group. Future research will focus on integrating intelligent optimization methods, such as deep reinforcement learning, to enhance the generalization ability of the control strategy in unstructured and dynamic environments.
Social force modelvicsek modelautonomous underwater vehicles (AUVs)swarm roboticsnavigation
Qiang Zhao、Bing Li、Gang Wang
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College of Mechanical and Control Engineering, Baicheng Normal University, No. 57, Zhongxing West Road, Aicheng 137000,P. R. China
College of Mechanical Engineering, Jilin Communications Polytechnic, No. 63 New Radio Street, Changchun 130012,P. R. China
NETL
NSTL
World Scientific
