Grasping perception method of space manipulator for complex scene task
Jiyang Yu, Dan Fei Huang, Jinyan Gao, Wenjie Li · 2023
Aiming at the problems such as illumination variation, occlusion interference, complex background and diversity of objects in the grasping process of space manipulator, a grasping perception method of space manipulator which can be used for real-time calculation was proposed. A hybrid algorithm strategy of long-distance gray feature search, lightweight detection network classification and lightweight segmentation network was adopted to obtain the centroid/position/attitude. First, when the end is far away from the target, the simple gray distribution feature is used in the field of view to detect whether the target is there or not, so as to quickly judge the area where the target is concerned. Then, the target area is extracted, and the lightweight deep convolution detection and recognition network is used in the process of close movement to carry out continuous recognition and classification of the target, determine the key parts to be captured, determine whether the target is an effective target, and constantly adjust to ensure that the target stays in the middle of the camera. Finally, when a relatively short distance is reached, the lightweight segmentation convolutional network is used to conduct semantic segmentation of the target, and the shape binarization data of multiple angles are obtained. In this way, the position and attitude information of the target are obtained according to the binocular stereo vision, and the feedback control computer is used to complete the fetching task. Compared with previous designs, the identification accuracy of the proposed method is increased by 1.4%, and the calculation speed is reduced by 58%. The simulation results show the effectiveness and adaptability of the proposed method.