Vision enhanced reactive locomotion control for trotting on rough terrain

Abstract

Legged robots have the potential to navigate in more challenging terrain than wheeled robots do. Unfortunately, their control is more difficult because they have to deal with the traditional mapping and path planning problems, as well as foothold computation, leg trajectories and posture control in order to achieve successful navigation. Many parameters need to be adjusted in real time to keep the robot stable and safe while it is moving. In this paper, we will present a new framework for a quadruped robot, which performs goal-oriented navigation on unknown rough terrain by using inertial measurement data and stereo vision. This framework includes perception and control, and allows the robot to navigate in a straight line forward to a visual goal in a difficult environment. The developed rough terrain locomotion system does not need any mapping or path planning: the stereo camera is used to visually guide the robot and evaluate the terrain roughness and an inertial measurement unit (IMU) is used for posture control. This new framework is an important step forward to achieve fully autonomous navigation because in the case of problems in the SLAM mapping, a reactive locomotion controller is always active. This ensures stable locomotion in rough terrain, by combining direct visual feedback and inertial measurements. By implementing this controller, an autonomous navigation system has been developed, which is goal-oriented and overcomes disturbances from the ground, the robot weight, or external forces. Indoor and outdoor experiments with our quadruped robot show the effectiveness and the robustness of this framework.