An efficient solution to the simultaneous localisation and mapping problem

Publisher:
Institute of Electrical and Electronic Engineering
Publication Type:
Conference Proceeding
Citation:
Proceedings of IEEE International Conference on Robotics and Automation - vol 1, 2002, pp. 406 - 411
Issue Date:
2002-01
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2004003404.pdf754.14 kB
Adobe PDF
This paper presents a novel approach to the simultaneous localisation and mapping algorithm that exploits the manner in which observations are fused into the global map of the environment to manage the computational complexity of the algorithm and improve the data association process. Rather than incorporating every observation directly into the global map of the environment, the constrained local submap filter relies on creating an independent, local submap of the features in the immediate vicinity of the vehicle. This local submap is then periodically fused into the global map of the environment using appropriately formulated constraints between the common feature estimates. This approach is shown to be effective in reducing the computational complexity of maintaining the global map estimates as well as improving the data association process.
Please use this identifier to cite or link to this item: