A Hierarchical Object Based Representation for Simultaneous Localization and Mapping
Conference Paper, Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems, Vol. 1, pp. 412 - 418, September, 2004
Abstract
Accomplishing simultaneous localization and mapping (SLAM) in very large city environments is a great challenge because of theoretical and practical issues on computational complexity, dynamic environment, representation and data association. In this paper, we describe practical algorithms for dealing with the representation issues. Feature-based, grid-based and direct methods are integrated into the framework of the hierarchical object based representation. The sampling and correlation based range image matching algorithm is developed to tackle the problem arising from uncertain, sparse and featureless data in outdoor environments. Experimental results of a 800 meter x 600 meter neighborhood demonstrate the feasibility of city-sized SLAM.
BibTeX
@conference{Wang-2004-9017,author = {Chieh-Chih Wang and Chuck Thorpe},
title = {A Hierarchical Object Based Representation for Simultaneous Localization and Mapping},
booktitle = {Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2004},
month = {September},
volume = {1},
pages = {412 - 418},
}
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.