Vision-based Monte-Carlo Localization for Humanoid Soccer Robots

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Author(s):	Almeida, Aislan C. ; Costa, Anna H. R. ; Bianchi, Reinaldo A. C. ; Todt, E ; Tonidandel, F Total Authors: 5
Document type:	Journal article
Source:	2017 LATIN AMERICAN ROBOTICS SYMPOSIUM (LARS) AND 2017 BRAZILIAN SYMPOSIUM ON ROBOTICS (SBR); v. N/A, p. 6-pg., 2017-01-01.
Abstract
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)

FAPESP's process:	16/21047-3 - ALIS: Autonomous Learning in Intelligent System
Grantee:	Anna Helena Reali Costa
Support Opportunities:	Regular Research Grants