Inertial-visual Collaborative Navigation Method for Master-slave Multi-lunar-based Equipment

This paper presents inertial-visual collaborative navigation method for master-slave multi-lunar-based equipment. Firstly, in view of the large uncertainty of the lunar environment, a multi-machine collaborative SLAM localization technology is proposed, which can enable the lunar equipment to build an environmental model and estimate its own motion without prior environmental information. Secondly, the global image operator is introduced to identify the common view area of the multi-lunar-based equipment, realize the information association among the multi-lunar-based equipment, and optimize the robustness of the visual navigation system to environmental changes such as illumination. Finally, the motion state information between the equipment is exchanged by radiocommunication, and the measured value is filtered and fused with the information obtained by inertial navigation system. The joint filtering model is used to simulate the information fusion process of the lunar-based equipment according to the weight of the allocation factor, which makes the target positioning more precision. The simulation results show that the proposed algorithm can further restrain the divergence of positioning errors and improve the positioning accuracy of the lunar-based equipment, which verifies the effectiveness of the proposed algorithm.