Multi-robot path planning using co-evolutionary genetic programming
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- @Article{Kala20123817,
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author = "Rahul Kala",
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title = "Multi-robot path planning using co-evolutionary
genetic programming",
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journal = "Expert Systems with Applications",
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volume = "39",
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number = "3",
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pages = "3817--3831",
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year = "2012",
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ISSN = "0957-4174",
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DOI = "doi:10.1016/j.eswa.2011.09.090",
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URL = "http://www.sciencedirect.com/science/article/pii/S0957417411014138",
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keywords = "genetic algorithms, genetic programming, Path
planning, Motion planning, Mobile robotics, Grammatical
evolution, Co-operative evolution, Multi-robot
systems",
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abstract = "Motion planning for multiple mobile robots must ensure
the optimality of the path of each and every robot, as
well as overall path optimality, which requires
cooperation amongst robots. The paper proposes a
solution to the problem, considering different source
and goal of each robot. Each robot uses a grammar based
genetic programming for figuring the optimal path in a
maze-like map, while a master evolutionary algorithm
caters to the needs of overall path optimality.
Co-operation amongst the individual robots'
evolutionary algorithms ensures generation of overall
optimal paths. The other feature of the algorithm
includes local optimisation using memory based lookup
where optimal paths between various crosses in map are
stored and regularly updated. Feature called wait for
robot is used in place of conventionally used priority
based techniques. Experiments are carried out with a
number of maps, scenarios, and different robotic
speeds. Experimental results confirm the usefulness of
the algorithm in a variety of scenarios.",
- }
Genetic Programming entries for
Rahul Kala
Citations