A Comparative Study of Three Mapping Methodologies

  • Authors:

  • X. Z. Zhang;A. B. Rad;Y. K. Wong;G. Q. Huang;Y. L. Ip;K. M. Chow

  • Affiliations:

  • Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, China;Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Hawthorn 3122, Australia;Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, China;Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, China;Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, China;Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, China

  • Venue:
  • Journal of Intelligent and Robotic Systems
  • Year:
  • 2007

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Abstract

Map building is one of the core competencies of truly autonomous robots. Numerous techniques have been developed to represent the static and dynamic environments as well as the perceptional sensing frameworks so far. In this paper, on the basis of our previous work, we compare various sensor systems in building the static and dynamic environment map with the segment-based map and Fuzzy-Tuned Grid-Based Map (FTGBM) strategies. From the comparative results of experiments, we propose a probably efficient and trade-off framework which balances the accuracy of the map against the overall system cost.