Generation of Optimal Coverage Paths for Mobile Robots Using Hybrid Genetic Algorithm
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- Schäfle Tobias Rainer
- Department of Mechanical Engineering, Toyohashi University of Technology
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- Mitschke Marcel
- Andreas Stihl AG & Co. KG
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- Uchiyama Naoki
- Department of Mechanical Engineering, Toyohashi University of Technology
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Abstract
<p>This paper presents new optimal offline approaches to solve the coverage path planning problem. A novel hybrid genetic algorithm (HGA), which uses, the turn-away starting point and backtracking spiral algorithms for performing local search, is proposed for grid-based environmental representations. The HGA algorithm is validated using the following three different fitness functions: the number of cell visits, traveling time, and a new energy fitness function based on experimentally acquired energy values of fundamental motions. Computational results show that compared to conventional methods, HGA improves paths up to 38.4%; moreover, HGAs have a consistent fitness for different starting positions in an environment. Furthermore, experimental results prove the validity of the fitness function.</p>
Journal
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- Journal of Robotics and Mechatronics
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Journal of Robotics and Mechatronics 33 (1), 11-23, 2021-02-20
Fuji Technology Press Ltd.
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Details 詳細情報について
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- CRID
- 1390850092193428352
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- NII Article ID
- 130007988334
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- NII Book ID
- AA10809998
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- ISSN
- 18838049
- 09153942
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- NDL BIB ID
- 032001065
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed