1. Precise Calibration: Remote Center of Motion Robot Computer Integrated Surgery II - Spring, 2011 Ryan Decker, Changhan Jun, Alex Vacharat, under Professor Dan Stoianovici URobotics Lab Introduction Quantify error in Polaris optical tracker Suggest improved measurement protocol Observe Revolving Needle Driver robot Correct RCM motion mechanically Improve targeting with optimized kinematic model Precise robot calibration requires very accurate motion tracking. To improve targeting, systems identification determines which parameters to add to the model and optimize. Outcomes and Results Polaris accuracy improves beyond any current estimate: RCM module is improved mechanically: Targeting is improved with 3 parameter optimization: Mechanical RCM correction improves targeting substantially, then parameter optimization takes accuracy slightly further The Problem Optical tracker measurements can be better - Current state-of-art puts Polaris error at 217µm RND robot has 3mm targeting error Above previously achieved 1.4mm targeting error Robot RCM behavior should more closely resemble the kinematic model (Euler angle formulation) Model is not trained to reflect current state of construction Better optical measurement protocol required to give more confidence in Polaris measurements Robot accuracy must be improved to be feasible for more dexterous clinical tasks Engineering Research Center for Computer Integrated Surgical Systems and Technology Taking more samples increases accuracy. Measurement quality decreases with distance from the tracker. The Solution Polaris accuracy quantified with large sample size, using CNC machine as 2µm accurate reference Develop C++ program for Polaris-CNC communication Offer suggestions to achieve better measurements Observe RND motion and correct axes offsets mechanically Develop MATLAB scripts to calculate axes locations Add physically intuitive parameters to kinematic model and optimize to improve targeting accuracy Develop MATLAB scripts to minimize error by adjusting kinematic parameters. Chosen parameters: α – Rx offset; β – Ry offset; Needle depth offset Publications Polaris poster accepted to: Engineering Urology Society conference In progress: Polaris paper to be submitted to MITAT Credits Ryan – Polaris; Changhan – CNC; Alex – Programming Support by and Acknowledgements Thank you to Russ Taylor, Doru Petrisor, Chunwoo Kim Lessons Learned Where to read in tracker volume How many samples to take Mechanical correction has limits Simplified systems ID will improve targeting Future Work Verification of Polaris data with other trackers Dissection-informed new kinematic model Table 1 (µm)XYZNorm Global Accuracy 1535190195 Global Precision 1353404408 Closest Point Accuracy 240555 Closest Point Precision 1627576 Table 2 (mm) Distance Between: Rx - Rz Rx – Needle path Rz – Needle path Before Correction 3.183.161.28 After Correction 0.60.770.43 Table 3α (deg)β (deg)Needle Offset (mm)Targeting Accuracy (mm) Before Optimization 00251.84 After Optimization -0.060.1222.341.3 Comparison of predicted and observed locations in targeting test