Sensing and gait planning of quadruped walking and climbing robot for traversing in complex environment

In this paper, a general study on improving adaptability of quadruped walking and climbing robot in complex environment is presented. First, a sensing system composed of range and gyroscope sensors in a novel arrangement is developed. By combining the sensing signals and the internal state of the robot, the surface geometry of the environment is sufficiently reconstructed in real-time. Secondly, a planning algorithm for the robot to overcome the reconstructed environment is conducted. Based on the reshaped surface, the planning algorithm not only provides the exact body trajectory and foot positions but also the adaptability of the robot in a specific environment. A method to improve the adaptability of the walking and climbing robot is also introduced. Thanks to the adherent ability of the robot, the center of gravity of the robot is allowed to move outside the support polygon to increase the reach-ability of the next swing leg. Finally, the effectiveness of the proposed approach is verified by the performances of the experiments in complex environments using a quadruped walking and climbing robot named MRWALLSPECT IV.