Convex Controller Synthesis for Robot Contact
This addresses stability and performance issues for deploying industrial robots in human-centric settings, though it appears incremental as it builds on robust control theory.
The paper tackled the challenge of controlling robot contacts in unstructured environments by proposing Convex Controller Synthesis (CCS), which outperformed classical controllers in physical interaction tasks like hand guiding and sliding on surfaces with unknown stiffnesses.
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.