A Robot Simulation System for Self-Location by Using Field Visual Information

Jian Rong Wang; Yang Yu; Jian Guo Wei; Mei Yu

doi:10.4028/www.scientific.net/AMR.748.690

Paper Titles

The Application of CRI Method in Fuzzy Reasoning
p.670

Fuzzy Recognition Intelligent System Based on Cash Character
p.675

The Research and Development of Automotive Switches Test System Based on LabVIEW
p.681

The Perception System of External World for Robot
p.685

A Robot Simulation System for Self-Location by Using Field Visual Information
p.690

Design of Obstacle Avoidance Detection Based on Substation Intelligent Inspection Robot
p.695

Study on Design Proposal of Computerized Numerical Control Machine Networking
p.699

A Linear Camera Calibration Applying in Servo Mechanical Arm System with One Camera
p.704

Sound Analysis and Synthesis for Audio Simulation System of Flight Simulator
p.708

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 748A Robot Simulation System for Self-Location by...

A Robot Simulation System for Self-Location by Using Field Visual Information

Abstract:

This Paper will introduce methods used to resolve self-location problem of humanoid robots. There are two method that will be mentioned in this paper. A traditional method which uses marks and flags on the soccer field for robot location will be introduced at first. This paper will also discuss how to solve the singularity problem in traditional self-location method. The optimization self-location method which uses sidelines on the soccer field will be introduced at the same time. This paper will introduce how to mapping the field sidelines in vision to the field sidelines of soccer field. This method is implemented and tested in Robocup 3D Soccer Simulation League. The results show that the accuracy of self-location method will be increased by taking full use of soccer field sidelines in vision information.

You might also be interested in these eBooks

Material and Manufacturing Technology IV

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 748)

Pages:

690-694

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.748.690

Citation:

Cite this paper

Online since:

August 2013

Authors:

Jian Rong Wang, Yang Yu, Jian Guo Wei, Mei Yu

Keywords:

Field Sideline, Humanoid, Robocup 3D, Robot Vision, Self-Location

Export:

RIS, BibTeX

Price:

Permissions:

Request Permissions

References

[1] Peter Stone. Layered Learning in Multi-Agent Systems,. School of Computer Science Carnegie Mellon University, December 15, (1998).

Google Scholar

[2] Hideaki Minakata, Yasuo Hayashibara, Katsuhiro Ichizawa, Takehito Horiuchi, Masahiro Fukuta, Shohei Fujita, Hiroshi Kaminage, el al. A Method of Single Camera Robocup Humanoid Robot Localization using Cooperation with Walking Control,. International Workshop on Advanced Motion Control - AMC, (2008).

DOI: 10.1109/amc.2008.4516040

Google Scholar

[3] Zhen Sun, Hong Huang, Xuemei Ren. Application of an Enhanced Location System with the Virtual MultiSensor,. WRI Global Congress on Intelligent Systems - GCIS, (2009).

DOI: 10.1109/gcis.2009.404

Google Scholar

[4] Bruno Sinopoli, Luca Schenato, Massimo Franceschetti, Kameshwar Poolla, Michael I. Jordan, Shankar S. Sastry. Kalman filtering with intermittent observations,. IEEE Transactions on Automatic Control - IEEE TRANS AUTOMAT CONTR , vol. 49, no. 9, pp.1453-1464, (2004).

DOI: 10.1109/tac.2004.834121

Google Scholar