Autonomous multilateral debridement with the Raven surgical robot

TLDR

Autonomous robot execution of surgical sub‑tasks can reduce surgeon fatigue and enable supervised tele‑surgery. This study introduces surgical debridement as a robotic sub‑task, demonstrates autonomous performance with the Raven robot, and reports experiments underscoring the importance of accurate state estimation. The system employs the Raven’s two 7‑DOF cable‑driven arms, stereo vision for 3‑D perception, trajopt optimization‑based motion planning, and model‑predictive control. Laboratory tests on 120 tissue fragments show robustness comparable to humans, with the dual‑arm system 1.5× faster than a single arm yet still slower than a human, highlighting the need for improved state estimation.

Abstract

Autonomous robot execution of surgical sub-tasks has the potential to reduce surgeon fatigue and facilitate supervised tele-surgery. This paper considers the sub-task of surgical debridement: removing dead or damaged tissue fragments to allow the remaining healthy tissue to heal. We present an autonomous multilateral surgical debridement system using the Raven, an open-architecture surgical robot with two cable-driven 7 DOF arms. Our system combines stereo vision for 3D perception with trajopt, an optimization-based motion planner, and model predictive control (MPC). Laboratory experiments involving sensing, grasping, and removal of 120 fragments suggest that an autonomous surgical robot can achieve robustness comparable to human performance. Our robot system demonstrated the advantage of multilateral systems, as the autonomous execution was 1.5× faster with two arms than with one; however, it was two to three times slower than a human. Execution speed could be improved with better state estimation that would allow more travel between MPC steps and fewer MPC replanning cycles. The three primary contributions of this paper are: (1) introducing debridement as a sub-task of interest for surgical robotics, (2) demonstrating the first reliable autonomous robot performance of a surgical sub-task using the Raven, and (3) reporting experiments that highlight the importance of accurate state estimation for future research. Further information including code, photos, and video is available at: http://rll.berkeley.edu/raven.