M2 Research Internship - Distributed optimization of heterogeneous multi-agent systems (MAS): Applications to multiple autonomous robots coordination

The research internship focuses on the development of a distributed optimization algorithm for multi-agent systems. Given the heterogeneity of each agent, the optimization problem is subject to non-identical constraints on different agents. The proposed algorithm should guarantee a predefined time convergence to the optimal state, which implies that the coordination will be achieved in a fixed time defined by the user, independently of the initial conditions. Compared to finite-time or fixed-time convergence, the proposed algorithm allows to explicitly fix the convergence time, thus providing better predictability and reliability of the optimization process. Furthermore, we plan to apply the theoretical results on an experimental testbed of the SmartLab platform (e.g., MiR100 mobile robots considering different constraints on each robot).