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A Vision Based System for Goal-Directed Obstacle Avoidance

  • Jan Hoffmann
  • Matthias Jüngel
  • Martin Lötzsch
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3276)

Abstract

We present a complete system for obstacle avoidance for a mobile robot. It was used in the RoboCup 2003 obstacle avoidance challenge in the Sony Four Legged League. The system enables the robot to detect unknown obstacles and reliably avoid them while advancing toward a target. It uses monocular vision data with a limited field of view. Obstacles are detected on a level surface of known color(s). A radial model is constructed from the detected obstacles giving the robot a representation of its surroundings that integrates both current and recent vision information. Sectors of the model currently outside the current field of view of the robot are updated using odometry. Ways of using this model to achieve accurate and fast obstacle avoidance in a dynamic environment are presented and evaluated. The system proved highly successful by winning the obstacle avoidance challenge and was also used in the RoboCup championship games.

Keywords

Free Space Mobile Robot Obstacle Avoidance Obstacle Detection Monte Carlo Localization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Jan Hoffmann
    • 1
  • Matthias Jüngel
    • 1
  • Martin Lötzsch
    • 1
  1. 1.Institut für Informatik, LFG Künstliche IntelligenzHumboldt-Universität zu BerlinBerlinGermany

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