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Proceedings Paper

Performance analysis for stable mobile robot navigation solutions
Author(s): Chris Scrapper Jr.; Raj Madhavan; Stephen Balakirsky
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Paper Abstract

Robot navigation in complex, dynamic and unstructured environments demands robust mapping and localization solutions. One of the most popular methods in recent years has been the use of scan-matching schemes where temporally correlated sensor data sets are registered for obtaining a Simultaneous Localization and Mapping (SLAM) navigation solution. The primary bottleneck of such scan-matching schemes is correspondence determination, i.e. associating a feature (structure) in one dataset to its counterpart in the other. Outliers, occlusions, and sensor noise complicate the determination of reliable correspondences. This paper describes testing scenarios being developed at NIST to analyze the performance of scan-matching algorithms. This analysis is critical for the development of practical SLAM algorithms in various application domains where sensor payload, wheel slippage, and power constraints impose severe restrictions. We will present results using a high-fidelity simulation testbed, the Unified System for Automation and Robot Simulation (USARSim).

Paper Details

Date Published: 16 April 2008
PDF: 12 pages
Proc. SPIE 6962, Unmanned Systems Technology X, 696206 (16 April 2008); doi: 10.1117/12.780022
Show Author Affiliations
Chris Scrapper Jr., National Institute of Standards and Technology (United States)
Raj Madhavan, National Institute of Standards and Technology (United States)
Stephen Balakirsky, National Institute of Standards and Technology (United States)

Published in SPIE Proceedings Vol. 6962:
Unmanned Systems Technology X
Grant R. Gerhart; Douglas W. Gage; Charles M. Shoemaker, Editor(s)

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