Formation obstacle avoidance control for multi-autonomous surface vehicle based on event triggered mechanism

The formation and obstacle avoidance control of multi-Agent systems, as an important research direction in the field of intelligent transportation, is widely applied in military and civilian environments due to its high practicality. The traditional periodic sampling update mechanism has limited effectiveness in handling non-ideal conditions and its high resource demand leads to significant system resource waste. To address this issue, this paper, using an autonomous surface vehicle model as a background, proposes a multi-Agent system formation consistency algorithm based on event-triggered control and the leader-follower method, incorporating a directed graph structure into the algorithm. Utilizing Lyapunov stability theory, this paper provides a rigorous mathematical proof of the stability of the proposed algorithm, demonstrating system stability while avoiding Zeno behavior. Furthermore, under the premise of maintaining formation consistency, this paper implements obstacle avoidance and collision avoidance functions using an improved artificial potential field method. Experimental results verify the significant advantages of the improved artificial potential field method in obstacle avoidance performance.