Obstacle avoidance for autonomous mobile robots based on position prediction using fuzzy inference

Takafumi Suzuki, Masaki Takahashi

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

6 Citations (Scopus)

Abstract

This study presents an obstacle avoidance method for Autonomous Mobile Robot by Fuzzy Potential Method (FPM) considering velocities of obstacles relative to the robot. The FPM, which is presented by Tsuzaki, is action control method for autonomous mobile robot. In the proposed method, to decide a velocity vector command of the robot to avoid moving obstacles safely, Potential Membership Function (PMF) considering time until colliding and relative velocity is designed. By means of considering predicted positions of the robot and the obstacle calculated from the time and the relative velocity, the robot can start avoiding behaviour at an appropriate time according to the velocity of the obstacle and the robot. To verify the effectiveness of the proposed method, numerical simulations and simplified experiment intended for an omni-directional autonomous mobile robot are carried out.

Original languageEnglish
Title of host publicationICINCO 2009 - 6th International Conference on Informatics in Control, Automation and Robotics, Proceedings
Pages299-304
Number of pages6
Publication statusPublished - 2009 Dec 1
EventICINCO 2009 - 6th International Conference on Informatics in Control, Automation and Robotics - Milan, Italy
Duration: 2009 Jul 22009 Jul 5

Publication series

NameICINCO 2009 - 6th International Conference on Informatics in Control, Automation and Robotics, Proceedings
Volume2 RA

Other

OtherICINCO 2009 - 6th International Conference on Informatics in Control, Automation and Robotics
Country/TerritoryItaly
CityMilan
Period09/7/209/7/5

Keywords

  • Autonomous mobile robot
  • Fuzzy potential method
  • Obstacle avoidance
  • Omni-directional mobile robot

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering

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