Vision-based Monte-Carlo Localization for Humanoid Soccer Robots

Autor(es)

Almeida, Aislan C. ; Costa, Anna H. R. ; Bianchi, Reinaldo A. C. ; Todt, E ; Tonidandel, F

• Tipo de documento: Artigo Científico
• Fonte: 2017 LATIN AMERICAN ROBOTICS SYMPOSIUM (LARS) AND 2017 BRAZILIAN SYMPOSIUM ON ROBOTICS (SBR); v. N/A, p. 6-pg., 2017-01-01.

Resumo

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. (AU)

• Processo FAPESP: 16/21047-3 - ALIS: Aprendizado Autônomo em Sistemas Inteligentes
• Beneficiário: Anna Helena Reali Costa
• Modalidade de apoio: Auxílio à Pesquisa - Regular