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Content Provider | IEEE Xplore Digital Library |
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Author | Yangming Li Olson, E.B. |
Copyright Year | 2010 |
Description | Author affiliation: University of Michigan, Department of Electrical Engineering and Computer Science, Ann Arbor, 48109, USA (Yangming Li; Olson, E.B.) |
Abstract | The detection of features from Light Detection and Ranging (LIDAR) data is a fundamental component of feature-based mapping and SLAM systems. Existing detectors tend to exploit characteristics of specific environments: corners and lines from indoor (rectilinear) environments, and trees from outdoor environments. While these detectors work well in their intended environments, their performance in different environments can be very poor. We describe a general purpose feature detector for LIDAR data that is applicable to virtually any environment. Our methods adapt classic feature detection methods from the image processing literature, specifically the multi-scale Kanade-Tomasi corner detector. Our resulting method is capable of identifying stable features at a variety of spatial scales and produces uncertainty estimates for use in a state estimation algorithm. We present results on standard datasets, including Victoria Park and Intel Research Center (both 2D), and the MIT DARPA Urban Challenge dataset (3D). |
Starting Page | 1388 |
Ending Page | 1393 |
File Size | 572456 |
Page Count | 6 |
File Format | |
ISBN | 9781424450381 |
ISSN | 10504729 |
DOI | 10.1109/ROBOT.2010.5509690 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2010-05-03 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Data mining Feature extraction Laser radar Detectors Computer vision Simultaneous localization and mapping Robots Robustness Image processing Uncertainty Corner Detector Robot navigation SLAM LIDARs Feature detection |
Content Type | Text |
Resource Type | Article |
Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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