Dynamic trajectory planning for mobile robot navigation in crowded environments

This paper describes a trajectory planning algorithm for mobile robot navigation in crowded environments; the aim is to solve the problem of planning a valid path through moving people. The proposed solution relies on an algorithm based on the Informed-RRT*, where the planner computes continuously a valid path to navigate in crowded environments. Our re-planning method allows to always obtain a feasible and optimal solution, while the robot executes the trajectory of the current path. Compared to other state of the art algorithms, our solution does not compute the entire path each time an obstacle is detected, but it evaluates the current solution validity, i.e., the presence of moving obstacles on the current path; in this case the algorithm tries to repair the current solution. Only if the current path is completely unacceptable, a new path is computed from scratch. Thanks to its reactivity, our solution always guarantees a valid path, that brings the robot to the desired goal position. We validated the proposed approach in a real case scenario where a mobile robot moves through human crowd in a safe and reliable way.