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Proceedings Paper

SLAM in a van
Author(s): Lewis A. Binns; Dimitris Valachis; Sean Anderson; David W. Gough; David Nicholson; Phil Greenway
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Paper Abstract

We have developed techniques for Simultaneous Localization and Map Building based on the augmented state Kalman filter, and demonstrated this in real time using laboratory robots. Here we report the results of experiments conducted out doors in an unstructured, unknown, representative environment, using a van equipped with a laser range finder for sensing the external environment, and GPS to provide an estimate of ground truth. The goal is simultaneously to build a map of an unknown environment and to use that map to navigate a vehicle that otherwise would have no way of knowing its location. In this paper we describe the system architecture, the nature of the experimental set up, and the results obtained. These are compared with the estimated ground truth. We show that SLAM is both feasible and useful in real environments. In particular, we explore its repeatability and accuracy, and discuss some practical implementation issues. Finally, we look at the way forward for a real implementation on ground and air vehicles operating in very demanding, harsh environments.

Paper Details

Date Published: 31 July 2002
PDF: 6 pages
Proc. SPIE 4729, Signal Processing, Sensor Fusion, and Target Recognition XI, (31 July 2002); doi: 10.1117/12.477627
Show Author Affiliations
Lewis A. Binns, BAE Systems (United Kingdom)
Dimitris Valachis, Univ. of Manchester Institute of Science and Technology (United Kingdom)
Sean Anderson, Univ. of Sheffield (United Kingdom)
David W. Gough, BAE Systems (United Kingdom)
David Nicholson, BAE Systems (United Kingdom)
Phil Greenway, BAE Systems (United Kingdom)


Published in SPIE Proceedings Vol. 4729:
Signal Processing, Sensor Fusion, and Target Recognition XI
Ivan Kadar, Editor(s)

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