A fast, accurate and uncalibrated robotic puncture method

Background: Robotic puncture system (RPS) consists of an optical tracking system (OTS) and a robotic arm gripping the puncture needle. Typically, the RPS requires hand-eye calibration before the surgery in order to obtain the relative position between the OTS and the robotic arm. However, if there is any displacement or angular deviation in either the robotic arm or the OTS, the calibration results become invalid, necessitating recalibration.

Methods: We propose an uncalibrated robotic puncture method that does not rely on the hand-eye relationship of the RPS. By constructing angle and position graph jacobian matrices respectively, and employing Square Root Cubature Kalman Filter for online estimation. This enables obtaining control variables for the robot to perform puncture operations.

Results: In simulation experiments, our method achieves an average error of 1.3495 mm and an average time consumption of 39.331 s.

Conclusions: Experimental results indicate that our method possesses high accuracy, low time consumption, and strong robustness.