Vidal's library
Title: Adaptive Robot Coordination using Interference Metrics
Author: Avi Rosenfeld, Gal A. Kaminka, and Sarit Kraus
Book Tittle: Proceedings of the AAMAS-04 Workshop on Learning and Evolution in Agent Based Systems
Year: 2004
Abstract: One key issue facing robotic teams is effective coordination mechanisms. Many robotic groups operate within domains where restrictions such as limiting areas of operation are liable to cause spatial conflicts between robots. Our previous work proposed a measure of coordination, interference, that measured the total time robots dealt with resolving such conflicts. We found that a robotic group s productivity was negatively correlated with interference: Effective coordination techniques minimized interference and thus achieved higher productivity. This paper uses this result to create adaptive coordination techniques that are able to dynamically adjust the efforts spent on coordination to match the number of perceived coordination conflicts in a group. Our robots independently calculate a projected level of interference they will encounter. By using this metric as a guide, we are able to create adaptive coordination methods that can quickly and effectively adjust to a given domain s spatial limitations. We present two adaptation heuristics that are completely distributed and require no communication between robots. Using thousands of simulated trials, we found that groups using these approaches achieved a statistically significant improvement in productivity over non-adaptive coordination methods.

Cited by 5  -  Google Scholar

@InProceedings{rosenfeld04a,
  author =	 {Avi Rosenfeld and Gal A. Kaminka and Sarit Kraus},
  title =	 {Adaptive Robot Coordination using Interference
                  Metrics},
  booktitle =	 {Proceedings of the {AAMAS-04} Workshop on Learning
                  and Evolution in Agent Based Systems},
  year =	 2004,
  abstract =	 {One key issue facing robotic teams is effective
                  coordination mechanisms. Many robotic groups operate
                  within domains where restrictions such as limiting
                  areas of operation are liable to cause spatial
                  conflicts between robots. Our previous work proposed
                  a measure of coordination, interference, that
                  measured the total time robots dealt with resolving
                  such conflicts. We found that a robotic group s
                  productivity was negatively correlated with
                  interference: Effective coordination techniques
                  minimized interference and thus achieved higher
                  productivity. This paper uses this result to create
                  adaptive coordination techniques that are able to
                  dynamically adjust the efforts spent on coordination
                  to match the number of perceived coordination
                  conflicts in a group. Our robots independently
                  calculate a projected level of interference they
                  will encounter. By using this metric as a guide, we
                  are able to create adaptive coordination methods
                  that can quickly and effectively adjust to a given
                  domain s spatial limitations. We present two
                  adaptation heuristics that are completely
                  distributed and require no communication between
                  robots. Using thousands of simulated trials, we
                  found that groups using these approaches achieved a
                  statistically significant improvement in
                  productivity over non-adaptive coordination
                  methods.},
  keywords =     {learning robots},
  url =		 {http://jmvidal.cse.sc.edu/library/rosenfeld04a.pdf},
  comment =	 {masrg},
  cluster = 	 {6099933472055950917}
}
Last modified: Wed Mar 9 10:16:12 EST 2011