Controlling contacts is truly challenging, and this has been a major hurdle to deploying industrial robots into unstructured/human-centric environments. More specifically, the main challenges are: (i) how to ensure stability at all times; (ii) how to satisfy task-specific performance specifications; (iii) how to achieve (i) and (ii) under environment uncertainty, robot parameters uncertainty, sensor and actuator time delays, external perturbations, etc. Here, we propose a new approach – Convex Controller Synthesis (CCS) – to tackle the above challenges based on robust control theory and convex optimization. In two physical interaction tasks – robot hand guiding and sliding on surfaces with different and unknown stiffnesses – we show that CCS controllers outperform their classical counterparts in an essential way.

生成讲解博客的中文版本

生成AI智能校验的中文版本