Abstract
In view of the need for acquiring tomato plant visual information for intelligent management in greenhouse, the method of tracking its main-stem based on visual servo technology was researched in this paper, which was supposed to improve the search efficiency for the targets, such as leaf, fruit and flower. According to the tomato factory-planted condition in the greenhouse, a binocular pan-tilt vision unit was designed, and the servo control method for tacking the main-stem was proposed, with which the bottom-up multi-views images were captured. Through matching the overlapped area of the adjacent images, the main-stem’ discrete images were spliced so that the plant morphology could be recovered. Finally the method was tested in greenhouse, and the results showed that the main-stem’s average splicing deviation was 3.77° in the height range from 600 to 1500 mm above the ground. The research result was supposed as a technical support for developing the robot for tomato pruning, harvesting and pollinating.
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Acknowledgements
We acknowledge that this work was financially supported by National Key Research and Development Plan (2019YFE0125200), and BAAFS Innovation Capacity Building Project (KJCX20210414).
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Feng, Q., Wang, X., Chen, J. (2022). Method of Visually Tracking Plant Main-Stem for Tomato’s Robotic Management. In: Yan, L., Duan, H., Yu, X. (eds) Advances in Guidance, Navigation and Control . Lecture Notes in Electrical Engineering, vol 644. Springer, Singapore. https://doi.org/10.1007/978-981-15-8155-7_207
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DOI: https://doi.org/10.1007/978-981-15-8155-7_207
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