A real-time low-computation cost human-following framework in outdoor environment for legged robots

Abstract Legged robots have potential advantages in mobility compared with wheeled robots. Hence, legged robots are widely utilized in outdoor unstructured environments. Human-following operation is one of important tasks for outdoor robots. However, most current human-following strategies requires large amount of computation resource hence difficult to be applied to legged robots. This paper proposes real-time low-computation cost human-following framework in outdoor environment for legged robots. Our method takes a full consideration of the differences between legged robots and wheeled robots. Firstly, an on-line extrinsic calibration method is proposed to calculate the camera coordinate and the world coordinate system. Then, a real-time low-computation cost human-following method utilizing RGBD cameras and 3D LIDAR is proposed. The robot motion considers tracking the leading person while avoiding obstacles. Furthermore, a dynamic alternating tripod trotting gait is developed to control the robot to follow the leading person. Finally, the method is implemented and tested on a hexapod robot Qingzhui with indoor and outdoor experiments. The framework proposed in this paper can be a valuable reference for other legged robots when operated in outdoor environments.