Name
Abstract | ||
|---|---|---|
In order to meet the requirement for automatic production, a pollination robot system for tomato flower on the inclined-wire culture was designed. The robot is composed of a platform vehicle, a binocular vision system, a manipulator with four degrees of freedom and an end-effector. Based on the tomato cultivation restriction, a collision-free motion of the manipulator was planned to move the end-effector to the spraying position without hitting the crop and the construction of the robot. The binocular vision system was used to detect the flower clusters according to the saturation & hue color feature and the size feature and obtain the 3-D spraying position of the flowers on the basis of stereoscopy. As the experimental results showed, the recognition success rate of the flower cluster was influenced by the number of flowers in one cluster: the recognition rate was only 50% for the cluster with one flower and the recognition rate was at least 80% for the cluster with no less than two flowers. The average error between the detected distance and measured distance for the spraying position accuracy was 6.4mm. The average spraying success rate of 69.6% was attributed to the leaves obstruction and the spraying direction deviation, and the execution time of the pollination operation was 15 seconds per cluster on average including both imaging time and spraying time. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICSAI.2016.7810939 | 2016 3rd International Conference on Systems and Informatics (ICSAI) |
Keywords | Field | DocType |
tomato flower,pollination robot,machine vision,path planning | Machine vision,Control theory,Computer science,Hue,Greenhouse,Artificial intelligence,Pollination,Motion planning,Computer vision,Binocular vision,Stereoscopy,Simulation,Robot | Conference |
ISSN | ISBN | Citations |
2474-0217 | 978-1-5090-5522-7 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ting Yuan | 1 | 43 | 4.83 |
| Shunlu Zhang | 2 | 0 | 0.34 |
| Xiyu Sheng | 3 | 0 | 0.34 |
| Dashuai Wang | 4 | 0 | 0.34 |
| Yue Gong | 5 | 0 | 0.68 |
| Wei Li | 6 | 436 | 140.67 |