Study on Convergent Consistency of Information Exchange in Massive Group Robots

Abstract

For the problem that information disorder and additional noises, as well as the instability of formation control in a massive-group-robot system, stops the system from achieving a good convergence state, a control algorithm based on the weight matrix stability of Kalman filtering is proposed. Through a robustness and uncertainty analysis, the uncertainty in information exchange in robots is transformed into an uncertain factor in nonlinear system. The Kalman filter helps to realize the convergent consistency of ideal state of robot system. The validity of this algorithm is proved by experiments.