3-D mapping of an underground mall using a tracked vehicle with four sub-tracks

Kazunori Ohno, Satoshi Tadokoro, Keiji Nagatani, Eiji Koyanagi, Tomoaki Yoshida

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

7 Citations (Scopus)

Abstract

The authors attempted to create a 3-D map of an underground mall and subway station using a tracked vehicle. This paper is a field report of the 3-D mapping of the Sendai subway station by the tracked vehicle in Dec. 2007. From the ticket barriers to the platform, the Sendai subway station consists of three floors. For the 3-D mapping, we developed a tracked vehicle named "Kenaf", a small and light-weight 3-D laser scanner called TK scanner, and a robust 3-D scan matching method. Kenaf can pass through ticket barriers and climb up and down stairs, while TK scanner has a wide view angle and can measure dense 3-D shapes. During the experiment, the robot stopped at different points and collected 3-D scan data. The 3-D shapes were recorded by the TK scanner as point clouds. These 3-D point clouds were integrated into a map on the basis of odometry data on-line. The constructed map was not correct because of the lack of robot position z and the odometry error. The 3-D map was constructed by matching these 3-D point clouds off-line. To increase the robustness of the matching, we used the iterative closest point (ICP) matching method with a gravity constraint.

Original languageEnglish
Title of host publication2009 IEEE International Workshop on Safety, Security and Rescue Robotics, SSRR 2009
DOIs
Publication statusPublished - 2009
Event2009 IEEE International Workshop on Safety, Security and Rescue Robotics, SSRR 2009 - Denver, CO, United States
Duration: 2009 Nov 32009 Nov 6

Publication series

Name2009 IEEE International Workshop on Safety, Security and Rescue Robotics, SSRR 2009

Other

Other2009 IEEE International Workshop on Safety, Security and Rescue Robotics, SSRR 2009
CountryUnited States
CityDenver, CO
Period09/11/309/11/6

Keywords

  • 3-D Mapping
  • 3-D laser scanner
  • Tracked vehicle
  • Underground mall

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Safety, Risk, Reliability and Quality

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