Time scales and stability in networked multi-robot systems

Abstract

This paper examines the dynamic interplay between decentralized controllers and mesh networking protocols for controlling groups of robots. A proportional controller is used to maintain robots in a formation based on estimates of the robots' states observed through the network. The state information is propagated through the network using a flooding algorithm, which introduces topology-dependent time delays. The coupled interaction of information flow over the network with the dynamics of the robots is modeled as a linear dynamical system. With this model it is shown that systems made up of robots with stable first order dynamics are stable for all network update times, positive feedback gains, and connected communication graphs. With higher order robot dynamics it is found that stability is a complex and counter intuitive function of feedback gain and network update time. A performance metric is proposed for analyzing the convergence rate of the multi-robot system. Experiments with flying quadrotor robots verify the predictions of the model and the performance metric.