کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6458908 | 1421120 | 2016 | 14 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: 3D pose estimation of green pepper fruit for automated harvesting 3D pose estimation of green pepper fruit for automated harvesting](/preview/png/6458908.png)
- Method for green pepper pose estimation is proposed.
- Fruit pose estimation is essential for automatic harvesting.
- Method uses model matching to fruit surface points.
- Surface points are obtained by laser range finder.
- Stem position for cutting can be calculated from fruit pose.
This paper presents a novel pose estimation algorithm for stem position detection in Japanese green pepper automatic harvesting. When the available visual cues do not provide sufficient information to the harvesting robot, information about the pose of the fruit in space is necessary for accurate stem position detection. In the proposed method the orientation of a fruit in space is obtained by fitting a model to surface points of the fruit. These surface points are acquired using a Lidar type laser range finder, and the point matching is performed using a coherent point drift algorithm with two model transformation methods, rigid and affine. The performance of the proposed method was evaluated both under laboratory conditions and in a greenhouse. In the laboratory test, the mean total error for the affine transformation was less than 25Â mm in 42 of 49 positions, less than 20Â mm in 28 of 49 positions and less than 15Â mm in 19 of 49 positions. For the rigid transformation, the same error was less than 25Â mm in 39 of 49 positions, less than 20Â mm in 31 of 49 positions and less than 15Â mm in 11 of 49 positions. The total error of the affine transformation was found to be proportional to the inclination angle, as the mean error was 11Â mm, 15Â mm, and 23Â mm for inclination angles of 15, 30 and 45 degrees, respectively. No relationship was found between the mean total error and the inclination angle for the rigid transformation, as the calculated mean total error was 20Â mm, 18Â mm, and 20Â mm for inclination angles of 15, 30 and 45 degrees, respectively. In the greenhouse test, the stem was calculated to be within the cutting range for 81 of 107 instances for affine transformation and for 66 of 107 for rigid transformation. These results suggest that the proposed method is suitable for stem position detection in the automatic harvesting of green pepper, and could be adjusted for use with other fruits and vegetables.
Journal: Computers and Electronics in Agriculture - Volume 128, October 2016, Pages 127-140