Aiming at the problem of difficulty in quickly and accurately estimating the pose of non-cooperative structures of satellites during the operation of space robotic arms, a neural radiation field based method for estimating and tracking the pose of non-cooperative key structures of satellites is proposed. This method first obtains the scene point cloud online through an RGBD camera, segments the point cloud to obtain satellite key structures, and then uses neural radiation fields to automatically establish a three-dimensional model of the key structures. Finally, based on the initial pose generation network and pose evaluation network, accurate pose estimation is obtained. An experimental platform consisting of an RGBD depth camera, a robotic arm, and a satellite model is constructed to conduct pose estimation experiments on key structures of satellites with different poses. The experimental results show that the algorithm proposed can automatically construct a 3D model of non-cooperative targets online without the need for human preparation of target data in advance. At the same time, it can effectively deal with target object occlusion and motion situations, thus achieving true non cooperative target pose estimation and tracking in spatial operations.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |