Dynamic Diffusion Maps-based Path Planning for Real-time Collision Avoidance of Mobile Robots

Given a route to a destination, a mobile robot still needs to locally plan a path to avoid collisions in continuously changing environment, e.g., a hall with pedestrians and moving obstacles. In this paper, diffusion maps are applied to find a local path for reaching a goal and avoiding collisions simultaneously. The proposed path planning algorithm plans a local path by utilizing a receding horizon approach, and therefore the algorithm repeats planning at every sample time. With this approach, mobile robots do not have to carry a prior map all the time because updated environment information is used for planning at every sample time. Extensive simulation is performed in different scenarios and demonstrates a good performance in collision avoidance.