Costmap Generation Based on Dynamic Obstacle Detection and Velocity Obstacle Estimation for Autonomous Mobile Robot

The environmental conditions corresponding to dangerous or collided areas are generally represented by Costmap when the Autonomous Mobile Robot (AMR) is navigated. Here, this paper provides a Costmap 2D layer plugin, Velocity Obstacle layer, it can accurately detect obstacle's coordination and radius and then estimate the obstacle's velocity to create Velocity Obstacle which can represent the potential collision vector in the future. In the simulation, we assume the robot's max velocity is 0.2m/s and an obstacle move forward to the robot with 0.3m/s. The results show the AMR can avoid the obstacle well. In experiment, the AMR also can avoid the people moving toward it in the real world.