Tangentbug Algorithm’s Application and Implementation in the NAO Avoidance

An Yuan Chen; Tong Wei Lu; Wen Jia He; Wen Ting Liu

doi:10.4028/www.scientific.net/AMR.926-930.3276

Paper Titles

Stereo Vision Based Distance Measurement and its Application
p.3258

Study on the Effectiveness Evaluation of the Weapon Equipment Based on Artificial Neural Network
p.3262

Sub-Nyquist Sampling for Short Pulse Based on Gabor Frame with B-Splines Windows
p.3266

Survey on Matting Algorithm
p.3270

Tangentbug Algorithm’s Application and Implementation in the NAO Avoidance
p.3276

Terrain Real-Time Rendering Based on Projected Grid and GPU Unsaturated Error Metric
p.3281

The Application of Nonlinear Modeling in the Fault Diagnosis of Fan
p.3286

The Impact of Complex Network Models to EDAs
p.3290

The Limits of Estimation of Distribution Algorithms
p.3294

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 926-930Tangentbug Algorithm’s Application and...

Tangentbug Algorithm’s Application and Implementation in the NAO Avoidance

Abstract:

Tangentbug algorithm requires the robot to select the moving point by the distance of the intersection of the partial scanned tangent picture, thus the algorithm is simple and of high real-time characteristics. Robot obstacle avoidance game is a regular event of FIRA ROBO WORLD CUP (Robot World Cup Soccer League). This article applies the Tangentbug algorithm into the obstacle avoidance by NAO robot, gets partial map information by NAO robot vision sensor, and analyzes and processes image information. By a few steps such as visual processing, corner extraction, distance conversion, direction calculation, and angle calculation, we get the motion paths of robot. The experimental results show that, Tangentbug can produce a shorter path in a short period of time.

You might also be interested in these eBooks

Progress in Applied Sciences, Engineering and Technology

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 926-930)

Pages:

3276-3280

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.926-930.3276

Citation:

Cite this paper

Online since:

May 2014

Authors:

An Yuan Chen*, Tong Wei Lu, Wen Jia He, Wen Ting Liu

Keywords:

Motion Path, Obstacle Avoidance, Partial Map Information, Tangentbug

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] W.L. Zhang: Adaptive mobile robot simultaneous localization and mapping algorithm(MS., University of Science and Technology of China, China 2009), p.18. (In Chinese).

Google Scholar

[2] S. Zhang: Research on recognition and localization of NAO robot (MS., Anhui University, China 2013), p.6. (In Chinese).

Google Scholar

[3] W. Pan: The method for multiple mobile robots map building research(MS., Central South University, China 2009), p.18. (In Chinese).

Google Scholar

[4] W.D. Ke,Z. C. Su and J. L. Li: Application Research of Computers, Vol. 27 (2010) No. 4, p.1216. (In Chinese).

Google Scholar

[5] W. H. Wang,W. D. Chen and G. Y. Xi: Robot, Vol. 23 (2011) No. 6, p.563. (In Chinese).

Google Scholar

[6] G.L. Zhang, X.M. Hu and J.F. Cai: Modern machinery, Vol. 12 (2011) No. 5, p.85. (In Chinese).

Google Scholar

[7] J. X. He and Z.M. Li: Application Research of Computers, Vol. 27 (2010) No. 8, p.2839. (In Chinese).

Google Scholar

[8] Z. X. Zhao,W. Nin and Z. G. Zhang: One for non-360-degree detection robot obstacle avoidance navigation algorithm , Vol. 46 (2010) No. 19, p.44. (In Chinese).

Google Scholar

[9] James Ng: A Practical Comparison of Robot Planning Algorithm Given Only Local Information (MS., The University of Western Australia, Australia 2005), p.35.

Google Scholar

[10] James Ng: An Analysis of Mobile Robot Navigation Algorithms in Unknown Environments(MS., The University of Western Australia, Australia 2010), p.28.

Google Scholar