Abstract: This paper studies the autonomous following random robots in a human-machine blending environment.Especially,a stable and effective method is presented for the robot to determine the desired following target and the recognition after the target is lost,that is,to achieve the visual tracking and positioning of pedestrians based on the image of stereo camera and point cloud data.Then,the location information of UWB is introduced to determine the target pedestrian,and a filter algorithm is used to fuse the sensor data to get the coordinate information under the camera coordinate system.Finally,the coordinate transformation is used to convert the location under the robot coordinate system.An improved dynamic window algorithm(MDWA) is also proposed to improve the following tasks performed by the robot.In addition,based on sensor data,a behaviour decision module including following behaviour,recovery behaviour and transition behaviour is proposed.Through the switching between behaviours,the robot can also retrieve the target when it is lost due to the turning of the target or the change of ambient lighting conditions which make the camera invalid.Experimental results show that the proposed following system can automatically determine the desired following target at starting up,and the robot can achieve good obstacle avoidance following in the scene with static obstacles or in the dynamic scene with other non-target pedestrian disturbances in the view.In particular,the robot can independently retrieve the following target in a turning scene or in a scene with varying lighting conditions,and the success rate of the robot in a turning scene is 81%.

Key words: Human-robot integration, Human following, Dynamic window, Navigation, Obstacle avoidance