Logistic Adaptive Controller with Overhead Reduction for Multirobot Systems

This article studies a real-time collaborative control problem of multirobot systems from the kinematics level. The main goal of the research is to reduce the nonessential overhead while improving the operational performance of the multirobot system. To this end, a logistic adaptive controller with event-triggered mechanism is developed to utilize the system’s resources more efficiently. By using only inputs that have a significant effect on the robot’s fore-and-aft behavior, a balance is established between reducing resource overhead and maintaining desired output. Meanwhile, the concepts of payoff and strategy in game theory are introduced to spontaneously describe the collaborative behavior of a multirobot system. It is then formulated as a dynamic quadratic programming problem by optimization method. The convergence of the proposed controller, the optimality of the strategies, and the Zeno-freeness of the triggering mechanism are proved theoretically in this article. Simulation results show that the proposed controller significantly reduces the communication and computational overhead required for the multirobot system.