Incremental and Robust Construction of Generalized Voronoi Graph (GVG) for Mobile Guide Robot

Sunghwan Ahn, Nakju Lett Doh, Kyoung Min Lee, Wan Kyun Chung

Research output: Contribution to conferencePaper

5 Citations (Scopus)

Abstract

GVG has been effectively used as a sensor based navigation tool using 360° sensor data. For mobile guide robot applications, however, we can only use 180° sensor data and the robustness of the navigation algorithm is critical for successful applications. For that purpose, the robot should be equipped with three capabilities. Those are 1) incremental GVG construction, 2) robust GVG navigation and 3) navigation strategy that just uses half of the sensor scan, i.e. 180°. In this paper, we propose a GVG navigation algorithm that has above 3 capabilities. We firstly propose a method that can estimate the invisible 180° range from previous range data. Moreover, we suggest a way of robust GVG navigation algorithm by using a sensor data matching technique. The simulation result validates that the proposed algorithm can incrementally and robustly navigate the semi-unstructured map by using 180° sensor scan.

Original languageEnglish
Pages3757-3762
Number of pages6
Publication statusPublished - 2003 Dec 26
Event2003 IEEE/RSJ International Conference on Intelligent Robots and Systems - Las Vegas, NV, United States
Duration: 2003 Oct 272003 Oct 31

Other

Other2003 IEEE/RSJ International Conference on Intelligent Robots and Systems
CountryUnited States
CityLas Vegas, NV
Period03/10/2703/10/31

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Cite this

Ahn, S., Doh, N. L., Lee, K. M., & Chung, W. K. (2003). Incremental and Robust Construction of Generalized Voronoi Graph (GVG) for Mobile Guide Robot. 3757-3762. Paper presented at 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, NV, United States.