A hFSM based cognitive control architecture for assistive task in R-MIS

This paper proposes a control architecture for surgical robotic assistive tasks in MIS using a hierarchical multi-level Finite State Machine (hFSM) as the cognitive control and a two-layered motion planner for the execution of the task. The hFSM models the operation starting from atomic actions to progressively build up more complex levels. The two-layer architecture of the motion planner merges the benefits of an offline geometric path construction method with those of online trajectory reconfiguration and reactive adaptation.