Vision-based Monte-Carlo localization for humanoid soccer robots
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2017-11-17
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ALMEIDA, A. C.
COSTA, A. H. R.
Reinaldo Bianchi
COSTA, A. H. R.
Reinaldo Bianchi
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Proceedings - 2017 LARS 14th Latin American Robotics Symposium and 2017 5th SBR Brazilian Symposium on Robotics, LARS-SBR 2017 - Part of the Robotics Conference 2017
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ALMEIDA, A. C.; COSTA, A. H. R.; BIANCHI, R. Vision-based Monte-Carlo localization for humanoid soccer robots. Proceedings - 2017 LARS 14th Latin American Robotics Symposium and 2017 5th SBR Brazilian Symposium on Robotics, LARS-SBR 2017 - Part of the Robotics Conference 2017, p. 1-6, Nov. 2017.
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© 2017 IEEE.In order to solve the self-localization problem, the Monte-Carlo Localization is proposed as a technique which is able to solve any localization problem. However, the implemented algorithm needs to be adapted to the robot and domain. Thus, this work presents a novel implementation for humanoid robots whose main sensory input is a camera, to be used in the domain of RoboCup Humanoid Soccer League. The paper proposes motion and observation models designed for the domain, and a method to determine the quantity of particles needed to represent the probability distribution. Finally, the proposals are validated by simulated experiments.