Target tracking plays an important role in the construction, operation, and maintenance of the space station by the robot, which puts forward high requirements on the accuracy of target tracking. However, the special space environment may cause complex non-Gaussian noise in target tracking data. And the performance of traditional Kalman Filter will deteriorate seriously when the error signals are non-Gaussian, which may lead to mission failure. In the paper, a novel Kalman Filter algorithm with Generalized Maximum Correntropy Criterion (GMCKF) is proposed to improve the tracking accuracy with non-Gaussian noise. The GMCKF algorithm, which replaces the default Gaussian kernel with the generalized Gaussian density function as kernel, can adapt to multi-type non-Gaussian noises and evaluate the noise accurately. A parameter automatic selection algorithm is proposed to determine the shape parameter of GMCKF algorithm, which helps the GMCKF algorithm achieve better performance for complex non-Gaussian noise. The performance of the proposed algorithm has been evaluated by simulations and the ground experiments. Then, the algorithm has been applied in the maintenance experiments in TianGong-2 space laboratory of China. The results validated the feasibility of the proposed method with the target tracking precision improved significantly in complex non-Gaussian environment.

Using space stations for a large number of observation, exploration, and research is a necessary way to fully develop space technology. It is a necessary means of space experiment to install the extravehicular experimental load by using the load plate. However, the extravehicular environment is full of danger, which poses a threat to the health and even safety of astronauts. Using robots to replace astronauts to complete this task can effectively reduce the threat to astronauts. Aiming at the problem that the configurations of existing space robots have difficulty in balancing the contradiction between complexity and dexterity, our previous work proposes a 12-DOF 3-arm robot and preliminarily explores the feasibility of its large-scale ability. This paper focus on the 8-DOF redundant dexterous manipulator composed of 2 of the robot arms. In view of the difficulties in solving the inverse kinematics of the redundant manipulator, the challenges of complex environmental lighting, and difficulties of matching multiple groups of holes and pins in the load plate assembly task, the research on the autonomous assembly of the load plate is carried out. The main work is as follows: (a) A variable D-H parameter inverse kinematics solution method is proposed, which lays a foundation for humanoid dexterous operation planning of the robot. (b) An autonomous operation method based on visual guidance and variable parameter admittance control is proposed. Finally, the safety and robustness of the robot in the autonomous assembly of the load plate with multipins and holes are successfully verified by experiments.