  This paper addresses the problem of cooperative transportation of an object
rigidly grasped by N robotic agents. We propose a 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 the workspace obstacles as well as that
they do not pass through singular configurations. The feasibility and
convergence analysis of the NMPC are explicitly provided. Finally, simulation
results illustrate the validity and efficiency of the proposed method.
