Real-time Data Driven Precision Estimator for RAVEN-II Surgical Robot End Effector Position
This addresses the need for high precision (≤1mm) in semi-autonomous abdominal surgeries, offering a cost-effective solution for surgical robots.
The paper tackled the problem of large position errors (up to 10mm) in the RAVEN-II surgical robot's end effector due to cable slack and gear backlash, proposing a real-time data-driven pipeline that reduced the error to around 1mm RMS across the workspace without needing high-resolution motion trackers.
Surgical robots have been introduced to operating rooms over the past few decades due to their high sensitivity, small size, and remote controllability. The cable-driven nature of many surgical robots allows the systems to be dexterous and lightweight, with diameters as low as 5mm. However, due to the slack and stretch of the cables and the backlash of the gears, inevitable uncertainties are brought into the kinematics calculation. Since the reported end effector position of surgical robots like RAVEN-II is directly calculated using the motor encoder measurements and forward kinematics, it may contain relatively large error up to 10mm, whereas semi-autonomous functions being introduced into abdominal surgeries require position inaccuracy of at most 1mm. To resolve the problem, a cost-effective, real-time and data-driven pipeline for robot end effector position precision estimation is proposed and tested on RAVEN-II. Analysis shows an improved end effector position error of around 1mm RMS traversing through the entire robot workspace without high-resolution motion tracker.