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A Simultaneous Localization and Mapping Algorithm in Complex Environments: SLASEM.
- Source :
-
Advanced Robotics . 2011, Vol. 25 Issue 6/7, p941-962. 22p. - Publication Year :
- 2011
-
Abstract
- In this paper we present an algorithm for the application of simultaneous localization and mapping in complex environments. Instead of building a grid map or building a feature map with a small number of the obstacles' geometric parameters, the proposed algorithm builds a sampled environment map (SEM) to represent a complex environment with a set of environment samples. To overcome the lack of one-toone correspondence between environment samples and raw observations, the signed orthogonal distance function is proposed to be used as the observation model. A method considering geometric constraints is presented to remove redundant environment samples from the SEM. We also present a method to improve the SEM's topological consistency by using corner constraints. The proposed algorithm has been verified in a simulation and an indoor experiment. The results show that the algorithm can localize the robot and build a complex map effectively. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01691864
- Volume :
- 25
- Issue :
- 6/7
- Database :
- Academic Search Index
- Journal :
- Advanced Robotics
- Publication Type :
- Academic Journal
- Accession number :
- 59906697
- Full Text :
- https://doi.org/10.1163/016918611X563373