Robotic odour search: Evolving a robot's brain with Genetic Programming
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- @InProceedings{Macedo:2017:ieeeICARSC,
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author = "Joao Macedo and Lino Marques and Ernesto Costa",
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booktitle = "2017 IEEE International Conference on Autonomous Robot
Systems and Competitions (ICARSC)",
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title = "Robotic odour search: Evolving a robot's brain with
Genetic Programming",
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year = "2017",
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pages = "91--97",
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month = apr # " 26-28",
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address = "Coimbra, Portugal",
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size = "7 pages",
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abstract = "This paper addresses the problem of controlling a
group of mobile robots to track an odour plume to its
source. To perform this task in real environments, it
is important that the robots are able to adapt to a
changing world, and use the experience gained to
improve their performance. We address this task with
Genetic Programming to evolve the controllers for the
robots. Two evolutionary approaches are proposed and
compared to a variant of the Silkworm Moth algorithm,
that has been modified to take advantage of multi robot
systems. The statistically validated results showed
that, in the groups of robots where significant
differences were found, the evolved controllers were
able to find the odour plume faster and converge to its
source better than the Silkworm Moth approach.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/ICARSC.2017.7964058",
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notes = "Also known as \cite{7964058}",
- }
Genetic Programming entries for
Joao Macedo
Lino Marques
Ernesto Costa
Citations