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- W2938110932 abstract "A coverage path planning algorithm is proposed for discrete harvesting in cashew orchards. The main challenge in such an orchard is the collection of fruits and nuts lying on the floor. The manual collection of fruits and nuts is both time consuming and labour intensive. The scenario begs for automated collection of fruits and nuts. There are methods developed in research for continuous crop fields, but none for discrete coverage. The problem is visualized as a graph traversal problem and paths for autonomous maneuvering are generated. A novel Mahalanobis distance based partitioning approach for performing coverage is introduced. The proposed path planner was able to achieve a mean coverage of 52.78 percentage with a deviation of 18.95 percentage between the best and worst solutions. Optimization of the generated paths is achieved through a combination of local and global search techniques. This was implemented by combining a discrete invasive weed optimization technique with an improved 2-Opt operator. A case study is formulated for the fruit picking operations in the orchards of Puducherry. The performance of the proposed algorithm is benchmarked against existing methods and also with performance metrics such as convergence rate, convergence diversity and deviation ratio. The convergence rate was observed to be 99.97 percent and 97.83 percent for a dataset with 48 and 442 nodes respectively. The deviation ratio was 0.02 percent and 2.16 percent, with a convergence diversity of 1.18 percent and 30.14 percent for datasets with 48 and 442 nodes. The achieved solutions was on par with the global best solutions achieved so far for the test datasets." @default.
- W2938110932 created "2019-04-25" @default.
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- W2938110932 date "2020-03-01" @default.
- W2938110932 modified "2023-09-25" @default.
- W2938110932 title "A hybrid weed optimized coverage path planning technique for autonomous harvesting in cashew orchards" @default.
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- W2938110932 doi "https://doi.org/10.1016/j.inpa.2019.04.002" @default.
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