STAF: Interaction-Based Design and Evaluation of Sensorized Terrain-Adaptive Foot for Legged Robot Traversing on Soft Slopes
Yao Chen, Guowei Shi, Peng Xu, Shipeng Lyu, Zhiyang Qiang, Zheng Zhu, Liang Ding, Zhenzhong Jia
- 发表年份
- 2024
- 引用次数
- 10
摘要
Legged robots have been widely used in unstructured field environments, where unforeseen nongeometric hazards, such as sinkage or slippage might compromise their mobility. Such uncertain terrain-related risks may be very challenging to mitigate by employing point or ball-shaped feet, however, determining the appropriate principles for foot design remains an open-research problem. This study presents a systematic pipeline of design and evaluations for the sensorized terrain-adaptive foot (STAF) aiming to remodel the underlying soft, sloped granular media. The advanced foot configuration enables explicit characterization of complex foot-terrain interaction responses, thereby facilitating evidence-based evaluations using proposed terrain physical metrics and terrain traveling metrics. These terrain-aware metrics are interpretable, physics-informed, and versatile for various robot prototypes. Compared to traditional empirical foot design methods, our model-based guideline can reliably identify physical terrain properties and explain contact behavior to optimize the foot sole's primary parameters. We conduct multiple experiments on both the single-foot testbed and a quadruped robot. The findings demonstrate that our developed STAF system significantly enhances mobility and in situ sensing capabilities over loose deformable slopes.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002