A combined planning and control strategy for mobile robots navigation in populated environments

In this work we present a combined planning and control strategy to let agile autonomous robots navigating in real-world populated environments by means of range limited sensors. In order to reduce the computational cost of obtaining a dynamically-feasible path, the proposed solution relies on a simple way-points generation subject to geometrical constraints. Conditions ensuring feasibility of the obtained trajectories also in the presence of possible exogenous disturbances such as wind are then derived by taking into account the interconnection between the vehicle dynamics, the low-level stabilizing controller and the trajectory planner. As an application, the navigation of a quadrotor and of a differential wheel robot in an unknown forest environment is proposed. In particular, the proposed framework is employed to let the vehicle moving at the highest possible speed that guarantees no collision with obstacles.