Caging in Motion: Characterizing Robustness in Manipulation through Energy Margin and Dynamic Caging Analysis
CoRR(2024)
摘要
To develop robust manipulation policies, quantifying robustness is essential.
Evaluating robustness in general dexterous manipulation, nonetheless, poses
significant challenges due to complex hybrid dynamics, combinatorial explosion
of possible contact interactions, global geometry, etc. This paper introduces
“caging in motion”, an approach for analyzing manipulation robustness through
energy margins and caging-based analysis. Our method assesses manipulation
robustness by measuring the energy margin to failure and extends traditional
caging concepts for a global analysis of dynamic manipulation. This global
analysis is facilitated by a kinodynamic planning framework that naturally
integrates global geometry, contact changes, and robot compliance. We validate
the effectiveness of our approach in the simulation and real-world experiments
of multiple dynamic manipulation scenarios, highlighting its potential to
predict manipulation success and robustness.
更多查看译文
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要