Reference : Ant-Air self-learning algorithm for path planning in a cluttered environment
Scientific congresses, symposiums and conference proceedings : Paper published in a journal
Engineering, computing & technology : Mechanical engineering
http://hdl.handle.net/10993/18000
Ant-Air self-learning algorithm for path planning in a cluttered environment
English
Ahmad, Rafiq mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Plapper, Peter mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Dec-2014
Applied Mechanics and Materials Journal
Yes
No
International
1660-9336
2nd International Conference on Control, Mechatronics and Automation
08-12-2014 to 10-12-2014
sponsored by International Association of Computer Science and Information Technology
Dubai
United Arabe Emirates (UAE)
[en] Path planning ; collision detection and avoidance ; self-learning algorithm ; assembling or disassembling ; narrow spaces
[en] Path planning in unstructured area while dealing with narrow spaces is an area of research which is receiving extensive interest. Many existing algorithms are able to produce safe paths but the presented concepts are either not adapted to narrow spaces or they are unable to learn from the past experience to improve repeated movements from the same agent or followed trajectories by other agents. This paper introduces an original concept based on Ant-Air phenomenon for safe path planning in a cluttered environment where narrow passages are treated. The algorithm presented is able to learn from the past experience and hence improve the already generated trajectory further by using some lessons learned from the past experience. The concept is applicable in various domains such as mobile robot path planning, manipulator trajectory generation and part movement in narrow passages in real or virtual assembly/disassembly process.
http://hdl.handle.net/10993/18000

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