Invariant filtering for simultaneous localization and mapping

Matthew Deans and Martial Hebert
IEEE International Conference on Robotics and Automation, April, 2000, pp. 1042-7.


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Abstract
This paper presents an algorithm for simultaneous localization and map building for a mobile robot moving in an unknown environment. The robot can measure only the bearings to identifiable targets and its own relative motion. The approach is to recursively estimate features of the environment which are invariant to the robot pose in order to decouple the pose error from the map error. The highly nonlinear nature of this problem requires more explicit reasoning about the spatial relationships between landmarks and between the robot and landmarks than those used in previous methods.

Keywords
localization, mapping

Notes
Number of pages: 6

Text Reference
Matthew Deans and Martial Hebert, "Invariant filtering for simultaneous localization and mapping," IEEE International Conference on Robotics and Automation, April, 2000, pp. 1042-7.

BibTeX Reference
@inproceedings{Deans_2000_3455,
   author = "Matthew Deans and Martial Hebert",
   title = "Invariant filtering for simultaneous localization and mapping",
   booktitle = "IEEE International Conference on Robotics and Automation",
   pages = "1042-7",
   month = "April",
   year = "2000",
}