Cooperative guidance of Lego Mindstorms NXT mobile robots

This paper presents experimental results of cooperative guidance laws embedded on Lego Mindstorms NXT mobile robots for two types of missions. The first one is navigation to a waypoint as a fleet with collision and obstacle avoidance, following a model predictive control (MPC) framework. The second one is source localization, i.e., finding the maximum of a potential field, for which a distributed estimation and control strategy is proposed. Experiments show the ability to perform the two missions on these basic mobile robots, in spite of their limited computational resources. In particular, the search for the optimal control sequence through a dedicated discretization of the command space makes it possible to implement real-time MPC.