To address the multi-task allocation problem of collaborative multi-automated guided vehicle (AGV) operations in automated loading systems, an adaptive multi-feature distributed k-Winners-Take-All (k-WTA) task allocation method is proposed. By integrating information such as AGV position, payload, battery level, and operational capacity, a task fitness evaluation model is constructed. Furthermore, by incorporating time-varying communication topologies and a data-driven adaptive gain, rapid and stable convergence is achieved in dynamic environments. A Power-arctan activation function is specifically designed to enhance the noise immunity of the system. Simulation results demonstrate that the proposed method can effectively suppress dynamic state oscillations, maintain fast and stable convergence performance under various topologies and swarm sizes, and realize effective multi-AGV task allocation.
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Share and Cite
Xu, Q., Zhang, Z., Chen, F., Dong, H., Wang, Z., Jiang, J. (2026) Adaptive Distributed k-WTA Network Under Time-varying Topologies for Multi-AGV Automated Loading Systems. Scientific Research Bulletin, 3(4), 6-19.