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Volume 11 Issue 2
April  2014
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Eric Lanteigne and Amor Jnifene. Biologically Inspired Node Generation Algorithm for Path Planning of Hyper-redundant Manipulators Using Probabilistic Roadmap. International Journal of Automation and Computing, vol. 11, no. 2, pp. 153-161, 2014. https://doi.org/10.1007/s11633-014-0777-6
Citation: Eric Lanteigne and Amor Jnifene. Biologically Inspired Node Generation Algorithm for Path Planning of Hyper-redundant Manipulators Using Probabilistic Roadmap. International Journal of Automation and Computing, vol. 11, no. 2, pp. 153-161, 2014. https://doi.org/10.1007/s11633-014-0777-6
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Biologically Inspired Node Generation Algorithm for Path Planning of Hyper-redundant Manipulators Using Probabilistic Roadmap

doi: 10.1007/s11633-014-0777-6

  • Department of Mechanical Engineering, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada;

  • Department of Mechanical and Aerospace Engineering, Royal Military College of Canada, Kingston, ON, K7K7B4, Canada

  • Received Date: 2013-04-11
  • Rev Recd Date: 2013-06-14
  • Publish Date: 2014-04-01
    Abstract
  • This article describes a biologically inspired node generator for the path planning of serially connected hyper-redundant manipulators using probabilistic roadmap planners. The generator searches the configuration space surrounding existing nodes in the roadmap and uses a combination of random and deterministic search methods that emulate the behaviour of octopus limbs. The strategy consists of randomly mutating the states of the links near the end-effector, and mutating the states of the links near the base of the robot toward the states of the goal configuration. When combined with the small tree probabilistic roadmap planner, the method was successfully used to solve the narrow passage motion planning problem of a 17 degree-of-freedom manipulator.

     

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