Classification of 3-D point cloud data that includes line and frame objects on the basis of geometrical features and the pass rate of laser rays

Kazunori Ohno, Takahiro Suzuki, Kazuyuki Higashi, Masanobu Tsubota, Eijiro Takeuchi, Satoshi Tadokoro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The authors aim at classification of 3-D point cloud data at disaster environment. In this paper, we proposed a method of classification for 3-D point cloud data using geometrical features and the pass rate of laser rays. Line and frame objects often trap robots, which causes the damages of sensors, motors, mechanical parts etc. at remote operation. Using our proposed method, the line and frame objects can be classified from the 3-D point cloud data. Key-point is use of the pass rate of laser rays. It is confirm that recognition rate of line and frame objects can be increased using the pass rate of laser rays. In addition, it is confirm that the proposed classification method works in the real scene. A training facility of Japan fireman department is used for the evaluation test because it is similar to the real disaster scene comparing the laboratory's test field.

Original languageEnglish
Title of host publicationField and Service Robotics - Results of the 8th International Conference
Pages527-540
Number of pages14
DOIs
Publication statusPublished - 2014
Event8th International Conference on Field and Service Robotics, FSR 2012 - Matsushima, Miyagi, Japan
Duration: 2012 Jul 162012 Jul 19

Publication series

NameSpringer Tracts in Advanced Robotics
Volume92
ISSN (Print)1610-7438
ISSN (Electronic)1610-742X

Other

Other8th International Conference on Field and Service Robotics, FSR 2012
Country/TerritoryJapan
CityMatsushima, Miyagi
Period12/7/1612/7/19

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Artificial Intelligence

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