A robust control strategy for mobile robots navigation in dynamic environments

This work introduces a novel control strategy to allow a class of mobile robots to robustly navigate in dynamics and potentially cluttered environments. The proposed approach combines a high-level motion planner and a low-level stabilizing feedback control law designed considering the nonlinear dynamic model of the vehicle. Taking advantage of a symbolic description of the vehicle dynamics and of the environment, the reference trajectories are sequences of elementary primitives which are obtained with a reduced computational cost. However, the resulting references may fail to be functionally controllable for the actual dynamical model of the vehicle. Accordingly, to obtain a desired tracking error, sufficient conditions are then derived by investigating the interconnection between the discrete time planner and the continuous time closed-loop nonlinear system. The effectiveness of the obtained results is demonstrated by considering, as application, a ground robot navigating in a cluttered environment.