The adaptation of a potential function controller for control of a dynamic multi-robot system

This thesis examines the issues of vehicle and information dynamics in the control of a multi-robot system using a radial-basis potential function controller. Distributed control of multi-robot systems requires each robot to communicate state information among the group for control of each robot. Many proposed distributed control methods for multi-robot systems assume that robots are modeled as holonomic vehicles and that perfect state information for each robot is available without delay. While these assumptions hold for slow-moving vehicles, as bandwidth increases, the vehicle and information dynamics must be accommodated.;In this thesis, a nonlinear rigid-body vehicle dynamic model is developed for a high-speed, skid-steered robot, and a nonlinear tire force model is implemented to provide realistic tire force saturation behavior. Empirical models of communication delay and error are modeled as functions of number of robots and message length using statistical models. Position uncertainty is modeled with a Gauss-Markov random walk. A simulation tool using these models is presented to examine the effects of physical and information dynamics, and to investigate ways to achieve high speed formation control. Local controllers for steering and slip control are developed in order to improve the stability and performance of the global potential function controller.;The DynaBot platform is introduced as an effective low-cost test bed for experiments to evaluate the role of nonholonomic vehicle dynamics and information dynamics on the control of dynamic multi-robot systems. The Dynabot uses GPS for sensing position, and each robot communicates its position to other robots through a wireless network. Experiments are performed using the DynaBot platform to evaluate potential function control of dynamic robots. Initial experiments with up to three robots show that the potential function controller can control a dynamic multi-robot system despite uncertainty due to GPS positioning, at average speeds up to 5 m/s (11 mph).