Hybrid topological/metric approach to SLAM

Kirill Kouzoubov; David Austin

doi:10.1109/robot.2004.1307259

Hybrid topological/metric approach to SLAM

Kirill Kouzoubov^*, David Austin

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

25 Citations (Scopus)

Abstract

We present a new topological/metric approach to solving the Simultaneous Localisation and Mapping problem. The map is represented as a graph - nodes are local map frames, and edges are transformations between adjacent map frames. The underlying local mapping algorithm is FastSLAM. The local maps and transformations are modelled by sets of particles. There is no global map frame, each map's uncertainties are restricted to its own map frame. The loop closing is achieved via efficient map matching. We demonstrate our algorithm running in real-time in an indoor environment using a laser range sensor.

Original language	English
Pages (from-to)	872-877
Number of pages	6
Journal	Proceedings - IEEE International Conference on Robotics and Automation
Volume	2004
Issue number	1
DOIs	https://doi.org/10.1109/robot.2004.1307259
Publication status	Published - 2004
Event	Proceedings- 2004 IEEE International Conference on Robotics and Automation - New Orleans, LA, United States Duration: 26 Apr 2004 → 1 May 2004

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10.1109/robot.2004.1307259

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AB - We present a new topological/metric approach to solving the Simultaneous Localisation and Mapping problem. The map is represented as a graph - nodes are local map frames, and edges are transformations between adjacent map frames. The underlying local mapping algorithm is FastSLAM. The local maps and transformations are modelled by sets of particles. There is no global map frame, each map's uncertainties are restricted to its own map frame. The loop closing is achieved via efficient map matching. We demonstrate our algorithm running in real-time in an indoor environment using a laser range sensor.

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M3 - Conference article

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Hybrid topological/metric approach to SLAM

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