AUTHOR=Zhu Hongwu , Wang Dong , Boyd Nathan , Zhou Ziyi , Ruan Lecheng , Zhang Aidong , Ding Ning , Zhao Ye , Luo Jianwen TITLE=Terrain-Perception-Free Quadrupedal Spinning Locomotion on Versatile Terrains: Modeling, Analysis, and Experimental Validation JOURNAL=Frontiers in Robotics and AI VOLUME=8 YEAR=2021 URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2021.724138 DOI=10.3389/frobt.2021.724138 ISSN=2296-9144 ABSTRACT=

Dynamic quadrupedal locomotion over rough terrains reveals remarkable progress over the last few decades. Small-scale quadruped robots are adequately flexible and adaptable to traverse uneven terrains along the sagittal direction, such as slopes and stairs. To accomplish autonomous locomotion navigation in complex environments, spinning is a fundamental yet indispensable functionality for legged robots. However, spinning behaviors of quadruped robots on uneven terrain often exhibit position drifts. Motivated by this problem, this study presents an algorithmic method to enable accurate spinning motions over uneven terrain and constrain the spinning radius of the center of mass (CoM) to be bounded within a small range to minimize the drift risks. A modified spherical foot kinematics representation is proposed to improve the foot kinematic model and rolling dynamics of the quadruped during locomotion. A CoM planner is proposed to generate a stable spinning motion based on projected stability margins. Accurate motion tracking is accomplished with linear quadratic regulator (LQR) to bind the position drift during the spinning movement. Experiments are conducted on a small-scale quadruped robot and the effectiveness of the proposed method is verified on versatile terrains including flat ground, stairs, and slopes.