Towards Safe Autonomous Surgical Tasks with Control Barrier Functions
Cristina Iacono, Paolino De Risi, Rocco Moccia, Bruno Siciliano, Fanny Ficuciello
Abstract
Safety is of utmost importance in surgical robots, as they operate in a complex and dynamic environment that directly impacts the patient’s health based on the surgical procedure’s success. One of the main difficulties in the control of surgical manipulators is in efficiently encoding dynamic nonlinear safety constraints into trajectory planning and robot control strategies. Control Barrier Functions (CBFs) represent a valuable control method for safety-critical environments such as the surgical one since its rigorous formulation aims at ensuring safety in controlled dynamic systems. This work represents a step forward in autonomous surgical task execution since it defines Lipschitz-continuous critical and autonomously prioritized dynamic constraints enforced through a CBF framework for the safe execution of surgical robotic tasks. The proposed framework, moreover, leverages Dual Quaternion (DQ) algebra for a unified and computationally efficient representation of geometric tasks and constraints, allowing for the straightforward definition of complex, time-varying surgical constraints. The safety framework is tested in simulation on the da Vinci Research Kit (dVRK) CoppeliaSim simulator and with the real dVRK robot in several surgical sub-tasks.