Communication-based Decentralized Cooperative Object Transportation Using Nonlinear Model Predictive Control

This paper addresses the problem of cooperative transportation of an object rigidly grasped by N robotic agents. We propose a decentralized Nonlinear Model Predictive Control (NMPC) scheme that guarantees the navigation of the object to a desired pose in a bounded workspace with obstacles, while complying with certain input saturations of the agents. The control scheme is based on inter-agent communication and is decentralized in the sense that each agent calculates its own control signal. Moreover, the proposed methodology ensures that the agents do not collide with each other or with workspace obstacles as well as that they do not pass through singular configurations. Finally, simulation results illustrate the validity and efficiency of the proposed method.