碩士 / 國立臺北大學 / 電機工程學系 / 103 / Complete area coverage navigation (CAC) requires a special type of robot path planning, where the robots should visit every point of the state workspace. CAC is an essential issue for cleaning robots and many other robotic applications. In addition to cleaning robots, plenty of robotics applications also require CAC, e.g. autonomous underwater coving vehicles, painter robots, lawn mowers, demining robots, automated harvesters, and window cleaners, etc. Real-time complete area coverage path planning is desirable for efficient performance in many applications. In this thesis, a novel vertical cell-decomposition (VCD) with minimum spanning tree (MST) approach is proposed for real-time CAC navigation of autonomous mobile robots. In this model, a vertical cell-decomposition (VCD) methodology and a spanning-tree based approach with minimum spanning tree are effectively integrated to plan a complete area coverage motion for autonomous mobile robot navigation. The computational complexity of this method with minimum trajectory length planned by a cleaning robot in the complete area coverage navigation with rectangle obstacles in the Euclidean space is O(n log n). The performance analysis, computational validation and comparison studies demonstrate that the proposal model is computational efficient, complete and robust.
| Identifer | oai:union.ndltd.org:TW/103NTPU0442001 |
| Date | January 2015 |
| Creators | Shao-Ting Shih, 施紹廷 |
| Contributors | Gene Eu Jan, 詹景裕 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | en_US |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 26 |
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