A faster path planner using accelerated particle swarm optimization

  • Authors:

  • Abdullah Zawawi Mohamed;Sang Heon Lee;Hung Yao Hsu;Namrata Nath

  • Affiliations:

  • Faculty of Engineering and Built Environment, School of Materials and Mechanical Engineering, National University of Malaysia (UKM), Bangi, Malaysia 43600 and Division of Information Technology, E ...;Division of Information Technology, Engineering and Environment, School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Mawson Lakes, Australia 5095;Division of Information Technology, Engineering and Environment, School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Mawson Lakes, Australia 5095;Division of Information Technology, Engineering and Environment, School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Mawson Lakes, Australia 5095

  • Venue:
  • Artificial Life and Robotics
  • Year:
  • 2012

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Abstract

The idea of placing small mobile robots to move around in a large building to detect potential intruders has been around for some time. However, there are still two major hurdles to overcome: to locate itself in the environment and to make a decision on how to move around safely and effectively at a reasonable computation cost. This paper describes a mathematical model for developing a scheme for an autonomous low cost mobile robot system using visual simultaneous localization and mapping and accelerated particle swarm intelligent path planner. The results indicated that this system could provide a solution for the problem of indoor mobile robot navigation. Advances in computer technology make this technique a cost effective solution for a future home service robot.