Enhancing self-similar patterns by asymmetric artificial potential functions in partially connected swarms

Giuliano Punzo, Derek James Bennet, Malcolm Macdonald

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

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The control of mobile robotic agents is required to be highly reliable. Artificial potential function (APF) methods have previously been assessed in the literature for providing stable and verifiable control, whilst maintaining a high degree of nonlinearity. Further, these methods can, in theory, be characterised by a full analytic treatment. Many examples are available in the literature of the employment of these methods for controlling large ensembles of agents that evolve into minimum energy configurations corresponding in many cases to regular lattices [1-2]. Although regular lattices can present naturally centric symmetry and self-similarity characteristics, more complex formations can also be achieved by several other means. In [3] the equilibrium configuration undergoes bifurcation by changing a parameter belonging to the part of artificial potential that couples the agents to the reference frame. In this work it is shown how the formation shape produced can be controlled in two further ways, resulting in more articulated patterns. Specifically the control applied is to alter the symmetry of interactions amongst agents, and/or by selectively rewiring interagent connections. In the first case, the network of connections remains the same, and may be fully connected.
Original languageEnglish
Title of host publicationTowards Autonomous Robotic Systems
PublisherInstitution of Engineering and Technology
ISBN (Print)978-3-642-23231-2
Publication statusPublished - 2 Sep 2011
EventTAROS 2011, 12th Conference Towards Automonous Robotic Systems - Sheffield, United Kingdom
Duration: 31 Aug 20112 Sep 2011

Publication series

NameLecture Notes in Artificial Intelligence


ConferenceTAROS 2011, 12th Conference Towards Automonous Robotic Systems
Country/TerritoryUnited Kingdom


  • asymmetric artificial potential functions
  • swarms
  • artificial Intelligence
  • robotic systems

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