Path planning of a mobile robot in a free-space environment using Q-learning-Reference-Cited by-同舟云学术

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Path planning of a mobile robot in a free-space environment using Q-learning

Published:2018-12-11 Issue:1 Volume:8 Page:133-142
ISSN:2192-6352
Container-title:Progress in Artificial Intelligence
language:en
Short-container-title:Prog Artif Intell

Author:

Jiang Jianxun,Xin Jianbin^ORCID

Funder

National Natural Science Foundation of China

the Key Scientific Research Project of Henan Higher Education

Postdoctoral Research Foundation of China

the Science&Technology Innovation Team Project of Henan Province

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

http://link.springer.com/content/pdf/10.1007/s13748-018-00168-6.pdf

Reference30 articles.

1. Raja, P., Pugazhenthi, S.: Optimal path planning of mobile robots: a review. Int. J. Phys. Sci. 7(9), 1314–1320 (2012)

2. Rezaee, H., Abdollahi, F.: A decentralized cooperative control scheme with obstacle avoidance for a team of mobile robots. IEEE Trans. Ind. Electron. 61(1), 347–354 (2013)

3. Parasuraman, S., Ganapathy, V., Shirinzadeh, B.: Multiple sensors data integration using MFAM for mobile robot navigation. In: IEEE Congress on Evolutionary Computation, pp. 2421–2427 (2007)

4. Cai, C., Ferrari, S.: Information-driven sensor path planning by approximate cell decomposition. IEEE Trans. Syst. Man Cybern. Part B Cybern. 39(3), 672–689 (2009)

5. Bhattacharya, S., Likhachev, M., Kumar, V.: Topological constraints in search-based robot path planning. Auton. Robots 33(3), 273–290 (2012)

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