On achievable accuracy for pose tracking

Abstract—This paper presents Cramér-Rao bound-like inequalities for pose tracking, which is defined as the problem of recovering the robot displacement given two successive readings of a relative sensor. Computing the exact Fisher Information Matrix (FIM) for pose tracking is hard, because the state comprises the map, which is infinite-dimensional and unknown. This paper shows that the FIM for pose tracking can be bounded by a function of the FIM for localization on a known map, thereby reducing the analysis to a finite-dimensional problem. The resulting bounds are independent of the map prior and representation. The results are valid for any relative sensor; the experimental verification is done for the particular case of pose tracking using range-finders (scan matching).

• Type: Conference
• Year: 2009
• Where: ICRA
• Authors: Andrea Censi
• Keywords: Cramér-Rao Bound-like Inequalities, ICRA 2009, Pose Tracking, Relative Sensor, Robotics