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A comparison of realtime obstacle avoidance methods for mobile robots

  • Section 6: Mobile Robots
  • Conference paper
  • First Online:
Experimental Robotics II

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 190))

Abstract

Recently several new dynamic approaches have been developed to enable a vehicle to autonomously avoid obstacles in its environment in real time. These algorithms are generally considered as reflexive collision avoidance algorithms since they are continuously using the latest update in sensory data and computing from this data error signals to drive and/or steer the vehicle away from a collision with the environment. This paper experimentally tested three of these methods, potential fields, generalized potential fields and vector field histograms, using a uniform set of hardware and software modules. The types of tests chosen were typical of navigation in an indoor environment and consisted of avoiding a single obstacle at high speed, travelling through a narrow hallway and passing through an open doorway. The main issues observed during the testing were, the maximum speed at which the vehicle could accomplish the test, the nature of the path taken by the vehicle during the test and any difficulties that arose in the process of implementing any of the algorithms.

NRC No. 31826

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Author information

Authors and Affiliations

  1. Autonomous Systems Laboratory, Institute for Information Technology, National Research Council of Canada, K1A 0R6, Ottawa, Ont, Canada

    Allan Manz (Graduate student), Ramiro Liscano & David Green

  2. University of Saskatchewan, S7N 0W0, Saskatoon Sk.

    Allan Manz (Graduate student)

Authors
  1. Allan Manz
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  2. Ramiro Liscano
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  3. David Green
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Editor information

Raja Chatila Gerd Hirzinger

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© 1993 Springer-Verlag London Limited

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Manz, A., Liscano, R., Green, D. (1993). A comparison of realtime obstacle avoidance methods for mobile robots. In: Chatila, R., Hirzinger, G. (eds) Experimental Robotics II. Lecture Notes in Control and Information Sciences, vol 190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0036147

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  • DOI: https://doi.org/10.1007/BFb0036147

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-19851-2

  • Online ISBN: 978-3-540-39323-8

  • eBook Packages: Springer Book Archive

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