1. Method for Determining Grasping Position and Angle of Sea Cucumber by Rotatable Bounding Box
- Author
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Xiufen Ye, Liu Wenzhi, Shuguo Xiao, and Chen Hao
- Subjects
Computer science ,business.industry ,04 agricultural and veterinary sciences ,02 engineering and technology ,Image segmentation ,Convolutional neural network ,Convolution ,Position (vector) ,Minimum bounding box ,040103 agronomy & agriculture ,0202 electrical engineering, electronic engineering, information engineering ,0401 agriculture, forestry, and fisheries ,020201 artificial intelligence & image processing ,Segmentation ,Computer vision ,Rectangle ,Artificial intelligence ,business ,Rotation (mathematics) - Abstract
It is a challenging task for a manipulator to grasp sea cucumber on the seabottom, because it is difficult to determine the sea cucumber grasping angle of the manipulator. In this paper, a method for determining grasping position and angle of sea cucumber by rotatable bounding box is proposed. Firstly, an improved full convolution image segmentation network model is proposed. Secondly, the expanded sea cucumber image is used to train the improved full convolution neural network. Thirdly, we use the trained neural network to segment the image to get the sea cucumber target. Finally, the grasping position and angle of sea cucumber are determined according to the minimum enclosing rectangle of the largest connected region of the segmented image. Experiments show that the improved full convolution image segmentation network model can effectively improve the accuracy and speed of sea cucumber target segmentation. The proposed method can determine the grasping position and angle of sea cucumber at any rotation angle in real time and accurately.
- Published
- 2019