Robust multi sensor pose estimation for medical applications

Andreas Tobergte, Mihai Pomarlan, Gerd Hirzinger
2009 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems  
In this paper a sensor fusion for pose estimation using optical and inertial data is presented. The proposed algorithm is based on extended Kalman filtering and fuses data from an optical tracking system and an inertial measurement unit. These two redundant sensor systems complement each other well, with the tracking system providing absolute positions and the inertial measurements giving low latency information of derivatives. Models for both sensors are given respecting the different sampling
more » ... times and latencies. Another key issue is to use information about every landmark, i.e. marker ball, visible for the tracking system, by coupling the two sensor systems tightly together. The algorithm is evaluated in simulation and tested with an experimental hardware platform. The combined sensor system is robust with respect to short time marker occlusions and effectively compensates for latencies in the pose measurements. 978-1-4244-3804-4/09/$25.00 ©2009 IEEE
doi:10.1109/iros.2009.5354696 dblp:conf/iros/TobergtePH09 fatcat:jdf5fxceybhlpgvs2jlwrvfx5i