Multi-Robot, Multi-Target Particle Swarm Optimization Search in Noisy Wireless Environments

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Multiple small robots (swarms) can work together using Particle Swarm Optimization (PSO) to perform tasks that are difficult or impossible for a single robot to accomplish. The problem considered in this paper is exploration of an unknown environment with the goal of finding a target(s) at an unknown location(s) using multiple small mobile robots. This work demonstrates the use of a distributed PSO algorithm with a novel adaptive RSS weighting factor to guide robots for locating target(s) in high risk environments. The approach was developed and analyzed on multiple robot single and multiple target search. The approach was further enhanced ... continued below

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Derr, Kurt & Manic, Milos May 1, 2009.

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Multiple small robots (swarms) can work together using Particle Swarm Optimization (PSO) to perform tasks that are difficult or impossible for a single robot to accomplish. The problem considered in this paper is exploration of an unknown environment with the goal of finding a target(s) at an unknown location(s) using multiple small mobile robots. This work demonstrates the use of a distributed PSO algorithm with a novel adaptive RSS weighting factor to guide robots for locating target(s) in high risk environments. The approach was developed and analyzed on multiple robot single and multiple target search. The approach was further enhanced by the multi-robot-multi-target search in noisy environments. The experimental results demonstrated how the availability of radio frequency signal can significantly affect robot search time to reach a target.

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  • 2nd IEEE International Conference on Human System Interaction,Catania, Italy,05/21/2009,05/23/2009

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  • Report No.: INL/CON-09-15308
  • Grant Number: DE-AC07-99ID-13727
  • Office of Scientific & Technical Information Report Number: 957551
  • Archival Resource Key: ark:/67531/metadc926228

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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  • May 1, 2009

Added to The UNT Digital Library

  • Nov. 13, 2016, 7:26 p.m.

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  • Dec. 6, 2016, 1:44 p.m.

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Derr, Kurt & Manic, Milos. Multi-Robot, Multi-Target Particle Swarm Optimization Search in Noisy Wireless Environments, article, May 1, 2009; [Idaho]. (digital.library.unt.edu/ark:/67531/metadc926228/: accessed December 13, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.