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4 May 1993 Comparison of two range-based pose estimators for a mobile robot
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Proceedings Volume 1831, Mobile Robots VII; (1993)
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States
Pose estimation, or self-location, is a fundamental requirement for a mobile robot which enables it to navigate along a planned path or to position itself within its environment. This paper compares two 2D pose estimation algorithms: one is feature-based, and the other is iconic. Both techniques match range data to a map to calculate x, y, and (theta) (the pose) of the range sensor within its 2D environment. The metrics for the comparison include accuracy, processing time, number of range data points, robustness to errors in the map, sensitivity to the initial rough pose estimate, and environmental models. The feature-based approach is better with respect to processing time and the initial estimate; the iconic method has the advantage with respect to accuracy, the number of data points, and the environment model. For the test environment used in this paper, both methods are robust to errors in the map. A hybrid approach is proposed which combines the two estimators in a way that exploits the advantages of both.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gary Shaffer, Javier Gonzalez, and Anthony Stentz "Comparison of two range-based pose estimators for a mobile robot", Proc. SPIE 1831, Mobile Robots VII, (4 May 1993);

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