Nonlinear Model Predictive Control of Omnidirectional Mobile Robot Formations

Abstract

In this paper we focus on solving a path following problem and keeping a geometrical formation. The problem of formation control is divided into a leader agent subproblem and a follower agent subproblem such that a leader agent follows a given path, while each follower agent tracks a trajectory, estimated by using the leader's information. In this paper, we exploit nonlinear model predictive control (NMPC) as a local control law due to its advantages of taking the robot constraints and future information into account. For the leader agent, we propose to explicitly integrate the rate of progression of a virtual vehicle into the local cost function of NMPC. This strategy can overcome stringent initial constraints in a path following problem. Our approach was validated by experiments using three omnidirectional mobile robots.