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Article Navigation> JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY> 2016> 25(4): 483-490
WANG Jun-zheng, QIAO Jia-nan, LI Jing. Effective approach for outdoor obstacle detection by clustering LIDAR data context[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2016, 25(4): 483-490. doi: 10.15918/j.jbit1004-0579.201625.0406
Citation: WANG Jun-zheng, QIAO Jia-nan, LI Jing. Effective approach for outdoor obstacle detection by clustering LIDAR data context[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2016, 25(4): 483-490.doi:10.15918/j.jbit1004-0579.201625.0406
shu

Effective approach for outdoor obstacle detection by clustering LIDAR data context

doi:10.15918/j.jbit1004-0579.201625.0406

  • Key Laboratory of Intelligent Control and Decision of Complex System, Beijing Institute of Technology, Beijing 100081, China

  • Received Date:2015-06-29
    Abstract
  • A method of environment mapping using laser-based light detection and ranging (LIDAR) is proposed in this paper. This method not only has a good detection performance in a wide range of detection angles, but also facilitates the detection of dynamic and hollowed-out obstacles. Essentially using this method, an improved clustering algorithm based on fast search and discovery of density peaks (CBFD) is presented to extract various obstacles in the environment map. By comparing with other cluster algorithms, CBFD can obtain a favorable number of clusterings automatically. Furthermore, the experiments show that CBFD is better and more robust in functionality and performance than the K-means and iterative self-organizing data analysis techniques algorithm (ISODATA).
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