Obstacle-Centered Trajectory Planning for Autonomous Mobile Robot

Trajectory planning enables Autonomous Mobile Robot (AMR) to have intelligence and avoid a collision in the interaction with obstacles. However, in scenes with multiple obstacles, most of the existing methods cannot minimize the collision risk. It is because that these methods do not distinguish the importance of the obstacles in the scene. Therefore, in this paper, we proposed an Obstacle-Centered Trajectory Planning (OCTP) method to solve the problem. In our method, a novel collision risk evaluation model is constructed, which considers the importance of each obstacle. In addition, a sliding-window-based key points interpolation method is used to smooth the velocity profile obeying constraints of collision risk and curvature. Finally, a comparison with the baseline method is performed. The experimental results show that the proposed method can effectively reduce AMR's collision risk in interacting with obstacles.