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2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications
A Practical Framework for Cleaning Robots
Penang, Malaysia
September 27-September 29
ISBN: 978-0-7695-4514-1
| ASCII Text | x | ||
| Wen-Mau Chong, Chien-Le Goh, Yoon-Teck Bau, "A Practical Framework for Cleaning Robots," Bio-Inspired Computing: Theories and Applications, International Conference on, pp. 97-102, 2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications, 2011. | |||
| BibTex | x | ||
| @article{ 10.1109/BIC-TA.2011.11, author = {Wen-Mau Chong and Chien-Le Goh and Yoon-Teck Bau}, title = {A Practical Framework for Cleaning Robots}, journal ={Bio-Inspired Computing: Theories and Applications, International Conference on}, volume = {0}, year = {2011}, isbn = {978-0-7695-4514-1}, pages = {97-102}, doi = {http://doi.ieeecomputersociety.org/10.1109/BIC-TA.2011.11}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Bio-Inspired Computing: Theories and Applications, International Conference on TI - A Practical Framework for Cleaning Robots SN - 978-0-7695-4514-1 SP97 EP102 A1 - Wen-Mau Chong, A1 - Chien-Le Goh, A1 - Yoon-Teck Bau, PY - 2011 KW - multiple cleaning robots KW - genetic algorithm KW - crossover KW - complete coverage path planning KW - unforeseen obstacles KW - unknown environment VL - 0 JA - Bio-Inspired Computing: Theories and Applications, International Conference on ER - | |||
This paper presents an extension to the pattern-based genetic algorithm for multiple cleaning robots to achieve complete coverage path planning in an unknown environment. The extension is formulated in the form of a framework which consists of four phases. The phases are scouting, task distribution, cleaning, and confirmation. The scouting phase allows the robots to scout in the initially unknown floor plan. The task distribution phase distributes cleaning tasks to multiple robots. The cleaning phase uses the pattern-based genetic algorithm with an added function to cater to unforeseen obstacles. The confirmation phaserecleans all the tiles. The performance of our proposed approach have been evaluated with six different floor plans through computer experiments. The cleaning phase performs better than the generic pattern-based genetic algorithm approach.
Index Terms:
multiple cleaning robots, genetic algorithm, crossover, complete coverage path planning, unforeseen obstacles, unknown environment
Citation:
Wen-Mau Chong, Chien-Le Goh, Yoon-Teck Bau, "A Practical Framework for Cleaning Robots," bic-ta, pp.97-102, 2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications, 2011
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