Decentralized Control of Uncertain Multi-Agent Systems with Connectivity Maintenance and Collision Avoidance
For multi-agent systems researchers, this work provides a decentralized solution to navigation control with safety guarantees under uncertainties, though it is incremental as it combines existing techniques.
This paper proposes a decentralized control protocol for uncertain nonlinear multi-agent systems that ensures connectivity maintenance, collision avoidance, and convergence to predefined positions using only local information. Simulation results validate the approach.
This paper addresses the problem of navigation control of a general class of uncertain nonlinear multi-agent systems in a bounded workspace of $\mathbb{R}^n$ with static obstacles. In particular, we propose a decentralized control protocol such that each agent reaches a predefined position at the workspace, while using only local information based on a limited sensing radius. The proposed scheme guarantees that the initially connected agents remain always connected. In addition, by introducing certain distance constraints, we guarantee inter-agent collision avoidance, as well as, collision avoidance with the obstacles and the boundary of the workspace. The proposed controllers employ a class of Decentralized Nonlinear Model Predictive Controllers (DNMPC) under the presence of disturbances and uncertainties. Finally, simulation results verify the validity of the proposed framework.