Motion Planning for Mobile Robot Obstacle Avoidance Using Optical Flow Images

Abstract

For autonomous navigation, mobile robots are required to avoid collisions with dynamic obstacles such as pedestrians. In a previous works, we have proposed a motion planner based on CNN with RGB and depth image inputs. In order for a robot to plan avoidance motions taking the moving direction of an obstacle into account, we propose a motion planner using optical flow images as the inputs. Through autonomous navigation, we show that the robot based on the motion planner is able to avoid not only dynamic obstacles, but also static obstacles.