Analysis and compensation of calibration errors in a multi-robot surgical platform
作者: Federico Vicentini, Paolo Magnoni, Matteo Giussani, Lorenzo Molinari Tosatti
摘要
A case study of multi-robot platform calibration is reported in the domain of robot-assisted neurosurgery. The robot system is composed of a hybrid parallel kinematic machine and 2 KUKA LWR arms and is dedicated to awake surgery with head motion compensation. The target accuracy is sub-millimeter. Calibration errors are known to cumulate along the kinematic loops in the system, so a method of volumetric compensation of inaccuracies is applied. Configuration-dependent compensation homogeneous transforms populate a look-up table trained offline for a set of discrete subregions of the workspace. At runtime, the compensation is applied to the robot motion so to reach an end-to-end static accuracy distributed with a median 0.75 mm and below 1 mm for the 95% of tests, with a 1∶36 reduction factor from the default calibration conditions.