An approach to ulta-tightly coupled data fusion for handheld input devices in robotic surgery

This paper introduces an ultra-tightly coupled approach to data fusion of optical and inertial measurements. The two redundant sensor systems complement each other well, with the cameras providing absolute positions and the inertial measurements giving low latency information of derivatives. The targeted application is the tracking of handheld input devices for robotic surgery, where landmarks are not always visible to all cameras. Especially when bi-manual operation is considered, where one hand can move between the other hand and a camera, occlusions occur frequently. The ultra-tighly coupled data fusion uses 2D-camera measurements to correct pose estimations in an extended Kalman filter without an explicit 3D-reconstruction. Therefore marker measurements are used to support the pose estimation, even if the marker is only visible in one camera. Experiments were done with an inertial measurement unit and rectified stereo cameras that show the advantage of the approach for the application.

[1]  Gerd Hirzinger,et al.  Planning and control of a teleoperation system for research in minimally invasive robotic surgery , 2009, 2009 IEEE International Conference on Robotics and Automation.

[2]  D. Simon Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches , 2006 .

[3]  Tobias Ortmaier,et al.  Telemanipulator for remote minimally invasive surgery , 2008, IEEE Robotics & Automation Magazine.

[4]  Dan Simon,et al.  Optimal State Estimation: Kalman, H∞, and Nonlinear Approaches , 2006 .

[5]  Emanuele Trucco,et al.  Introductory techniques for 3-D computer vision , 1998 .

[6]  T. Başar,et al.  A New Approach to Linear Filtering and Prediction Problems , 2001 .

[7]  Ravindra Babu,et al.  Ultra-Tight GPS/INS/PL Integration: Kalman Filter Performance Analysis , 2005 .

[8]  Robert M. Haralick,et al.  Review and analysis of solutions of the three point perspective pose estimation problem , 1994, International Journal of Computer Vision.

[9]  Henrik I. Christensen,et al.  Wiimote robot control using human motion models , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  G Hirzinger,et al.  Development of actuated and sensor integrated forceps for minimally invasive robotic surger , 2005, The international journal of medical robotics + computer assisted surgery : MRCAS.

[11]  S. F. Schmidt APPLICATION OF STATISTICAL FILTER THEORY TO THE OPTIMAL ESTIMATION OF POSITION AND VELOCITY ON BOARD A CIRCUMLUNAR VEHICLE , 2022 .

[12]  Alin Albu-Schäffer,et al.  DLR MiroSurge: a versatile system for research in endoscopic telesurgery , 2010, International Journal of Computer Assisted Radiology and Surgery.

[13]  Salah Sukkarieh,et al.  Tightly Coupled INS/GPS with Bias Estimation for UAV Applications , 2004 .

[14]  Bernhard Kübler,et al.  Development of actuated and sensor integrated forceps for minimally invasive robotic surgery , 2006 .

[15]  Gerd Hirzinger,et al.  Robust multi sensor pose estimation for medical applications , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  Gerd Hirzinger,et al.  Prototypic Force Feedback Instrument for Minimally Invasive Robotic Surgery , 2008 .

[17]  Alin Albu-Schäffer,et al.  The DLR MIRO: a versatile lightweight robot for surgical applications , 2008, Ind. Robot.

[18]  Jinling Wang,et al.  Kalman Filter Design Strategies for Code Tracking Loop in Ultra-Tight GPS/INS/PL Integration , 2006 .