Repositório do Conhecimento Institucional do Centro Universitário FEI
 

Vision-based Monte-Carlo localization for humanoid soccer robots

N/D

Tipo de produção

Artigo de evento

Data de publicação

2017-11-17

Periódico

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

Editor

Citações na Scopus

3

Autores

ALMEIDA, A. C.
COSTA, A. H. R.
Reinaldo Bianchi

Orientadores

Resumo

© 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.

Citação

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.

Palavras-chave

Keywords

Assuntos Scopus

Humanoid robot; Humanoid soccer robots; Localization problems; Monte Carlo localization; Observation model; Self localization; Sensory input; Simulated experiments

Coleções

Avaliação

Revisão

Suplementado Por

Referenciado Por