<p>Aiming at the requirements of formation stability and task adaptability of multi-autonomous guided vehicle (AGV) systems in dynamic scenarios within complex environments, this paper proposes a distributed adaptive formation reconfiguration framework based on a triggering mechanism. This framework breaks through the communication bottleneck of traditional centralized control and realizes real-time reconfiguration of the formation topology through local information interaction and a dynamic decision-making mechanism. Theoretically, a topology model is constructed to describe the communication and cooperation relationships among AGVs, and a distributed behavior-based control algorithm is designed to achieve the formation and maintenance of the leader–follower formation. Trigger rules are utilized to dynamically adjust the topological structure to adapt to complex channel environments. Finally, the convergence of the system is proved by the Lyapunov stability theory. Simulation and experimental results show that the proposed method can effectively improve the traffic efficiency of multi-AGV in complex channels, reduce the collision rate, and has significant advantages compared with traditional methods. Specifically, compared with conventional artificial potential field (APF) methods, the proposed approach reduces the average formation error by 32% and improves collision-free success rate by 28% in narrow-channel scenarios, while maintaining a 40% faster convergence speed during topology reconfiguration.</p>