Perception for Collaborative Robots in Pruning Operations
In this work a set of novel approaches based on well-known computer vision techniques is proposed to deal with the autonomous perception part of an HRI robotic system. In the considered scenario, a human-robot duo interact to plan maintenance and pruning operations in a vineyard. Once the human expe...
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| Published in: | 2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA) pp. 01 - 04 |
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| Main Authors: | , , , , , |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
IEEE
10-09-2024
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | In this work a set of novel approaches based on well-known computer vision techniques is proposed to deal with the autonomous perception part of an HRI robotic system. In the considered scenario, a human-robot duo interact to plan maintenance and pruning operations in a vineyard. Once the human expert has selected a set of branches to cut in the approximate area, the robot stores this information in order to be able to return later, identify the branches and cut them at an adequate point. This is achieved by producing models of the plant by segmenting the view through a combination of intensity and depth data, using RGB-D camera sensors. This segmentation is fed back into the pipeline, used as a base mask to identify parts of the plant through watershed segmentation, and identifying the branches and gems in the segmented images. The proposed method was develop based on real data, and tested in experimental scenarios with the real robot. |
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| ISSN: | 1946-0759 |
| DOI: | 10.1109/ETFA61755.2024.10711130 |