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International Conference on Principles and Practice of Multi-Agent Systems

PRIMA 2014: PRIMA 2014: Principles and Practice of Multi-Agent Systems pp 190–205Cite as

Intelligent Collision Avoidance between Autonomous Agents Using Adaptive Local Views

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8861))

Abstract

We propose a nature-inspired, intelligent collision management approach for use by multiple autonomous agents. This approach is calculated by each agent involved in possible collision through its own local view and without communication with other agents or central control. The approach uses both the current position and the velocity of other local agents to compute a future trajectory in order to both predict collision and avoid it. Our approach is capable of dealing with static obstacles and is developed in conjunction with a common kinematics metric ‘Minimal Predicted Distance (MPD)’ ensuring all agents remain free of collision while attempting to follow their goal direction, thus making the procedure well-suited for real-time applications. We build on prior work related to rectangular roundabout (‘rectabout’) and introduce the concept of hybrid rectabout for collision avoidance that takes into account heterogeneous agents, i.e. variable speed and variable size. Each agent has its own speed (and local view), and senses its surroundings and acts independently without central coordination or communication with other agents. We apply our hybrid rectabout maneuver to WowWee Rovio mobile robots and provide both analytic and empirical results to show that our fully decentralized, non-communicative and distributed approach generates collision-free motions.

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Author information

Authors and Affiliations

  1. School of Computing and Mathematical Sciences, Auckland University of Technology, New Zealand

    Fan Liu & Ajit Narayanan

Authors
  1. Fan Liu
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  2. Ajit Narayanan
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Editor information

Editors and Affiliations

  1. School of Computer Science and Software Engineering, University of Wollongong, Northfields Avenue, 2522, Wollongong, NSW, Australia

    Hoa Khanh Dam

  2. Imperial College, SW7 2BT, London, UK

    Jeremy Pitt

  3. University of Electronic Science and Technology of China, 610051, Chengdu, Sichuan, China

    Yang Xu

  4. NICTA Queensland Research Laboratory, GPO Box 2434, 4001, Brisbane, QLD, Australia

    Guido Governatori

  5. Nagoya Institute of Technology, Gokiso-cho, 466-8555, Showa-ku, Nagoya, Japan

    Takayuki Ito

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© 2014 Springer International Publishing Switzerland

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Liu, F., Narayanan, A. (2014). Intelligent Collision Avoidance between Autonomous Agents Using Adaptive Local Views. In: Dam, H.K., Pitt, J., Xu, Y., Governatori, G., Ito, T. (eds) PRIMA 2014: Principles and Practice of Multi-Agent Systems. PRIMA 2014. Lecture Notes in Computer Science(), vol 8861. Springer, Cham. https://doi.org/10.1007/978-3-319-13191-7_16

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  • DOI: https://doi.org/10.1007/978-3-319-13191-7_16

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13190-0

  • Online ISBN: 978-3-319-13191-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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