TY - GEN
T1 - Proprioception and Tail Control Enable Extreme Terrain Traversal by Quadruped Robots
AU - Yang, Yanhao
AU - Norby, Joseph
AU - Yim, Justin K.
AU - Johnson, Aaron M.
N1 - This research was sponsored by the Army Research Office under Grant Number W911NF-19-1-0080 and the National Science Foundation under Grant Number CCF-2030859 to the Computing Research Association for the CIFellows Project. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Office, the National Science Foundation, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.
PY - 2023
Y1 - 2023
N2 - Legged robots leverage ground contacts and the reaction forces they provide to achieve agile locomotion. However, uncertainty coupled with contact discontinuities can lead to failure, especially in real-world environments with unexpected height variations such as rocky hills or curbs. To enable dynamic traversal of extreme terrain, this work introduces 1) a proprioception-based gait planner for estimating unknown hybrid events due to elevation changes and responding by modifying contact schedules and planned footholds online, and 2) a two-degree-of-freedom tail for improving contact-independent control and a corresponding decoupled control scheme for better versatility and efficiency. Simulation results show that the gait planner significantly improves stability under unforeseen terrain height changes compared to methods that assume fixed contact schedules and footholds. Further, tests have shown that the tail is particularly effective at maintaining stability when encountering a terrain change with an initial angular disturbance. The results show that these approaches work synergistically to stabilize locomotion with elevation changes up to 1.5 times the leg length and tilted initial states.
AB - Legged robots leverage ground contacts and the reaction forces they provide to achieve agile locomotion. However, uncertainty coupled with contact discontinuities can lead to failure, especially in real-world environments with unexpected height variations such as rocky hills or curbs. To enable dynamic traversal of extreme terrain, this work introduces 1) a proprioception-based gait planner for estimating unknown hybrid events due to elevation changes and responding by modifying contact schedules and planned footholds online, and 2) a two-degree-of-freedom tail for improving contact-independent control and a corresponding decoupled control scheme for better versatility and efficiency. Simulation results show that the gait planner significantly improves stability under unforeseen terrain height changes compared to methods that assume fixed contact schedules and footholds. Further, tests have shown that the tail is particularly effective at maintaining stability when encountering a terrain change with an initial angular disturbance. The results show that these approaches work synergistically to stabilize locomotion with elevation changes up to 1.5 times the leg length and tilted initial states.
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U2 - 10.1109/IROS55552.2023.10342384
DO - 10.1109/IROS55552.2023.10342384
M3 - Conference contribution
AN - SCOPUS:85174562440
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 735
EP - 742
BT - 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023
Y2 - 1 October 2023 through 5 October 2023
ER -