Name
Abstract | ||
|---|---|---|
In this paper, we present a novel autonomous peach-harvesting approach. The robot can autonomously move around the tree and detect the peaches accurately by a well-designed fully connected neural network, adapting to different illumination. Next, the robot generates a score for each peach, taking into account the confidence of the classification and the size of the bounding box, and then pick one of the most suitable peach. In order to track the peach more robustly and quickly, we choose the KCF tracking algorithm. Finally, the robot picks the peach through a 6-DOF manipulator. In addition, we propose a monocular high-precision ranging method based on structured light. The cost of our method is lower than the traditional ranging method, which enables the robot to obtain the accurate spatial position of the peach. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICACI.2018.8377546 | 2018 Tenth International Conference on Advanced Computational Intelligence (ICACI) |
Keywords | Field | DocType |
robot,harvesting,peach,manipulator,detection,measurement,segmentation | Computer vision,Structured light,Computational intelligence,Segmentation,Computer science,Ranging,Artificial intelligence,Artificial neural network,Robot,Monocular,Minimum bounding box | Conference |
ISBN | Citations | PageRank |
978-1-5386-4363-1 | 0 | 0.34 |
References | Authors | |
2 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yongjia Yu | 1 | 0 | 0.34 |
| Zengpeng Sun | 2 | 0 | 0.34 |
| Xiaoguang Zhao | 3 | 54 | 18.68 |
| Jiang Bian | 4 | 897 | 61.74 |
| Xiaolong Hui | 5 | 1 | 1.04 |