On 2024 June 2, Chang’e 6 landed on the edge of the Apollo Crater on the lunar far side and conducted surface and subsurface sampling. This study used instruments on the lander to determine the mechanical parameters of lunar soil and provide a basis for surface sampling. Data collected by monitoring cameras A and B on the lander were used to analyze the indentation mark made by the contact sensor on the robotic arm during surface sampling. The geometric parameters of these indentation marks were extracted using point-cloud image-processing technology. On a surface sampling test platform based on the actual dimensions of Chang’e 6, indentation tests were performed using the contact-sensor component with a prepared lunar soil simulant, resulting in 24 sets of test data. To determine the state of the lunar soil, the least-squares method was applied, with the depth, length, surface area, and pressure of the contact indentations as input parameters and the 3 states of the lunar soil simulant as the output parameters. Finally, Chang’e 6 conducted 3 contact operations on the lunar far side. Custom indentation processing software yielded depths of 11.56, 11.31, and 8.33 mm for the 3 impressions. The soil at these sampling sites was identified as loose, and the recommended scooping depths were 25, 25, and 22 mm, which were close to the actual scooping depths (21.2, 25, and 23.6 mm, respectively) obtained from on-Moon telemetry data, proving the feasibility of this method.

Generating selfie images on the surface of a celestial body poses several challenges, including the position of the robotic arm, camera field of view, and limited shooting time. To address these challenges, the PCMIS (3D Point Cloud Matching Based Image Stitching) algorithm is designed, along with a corresponding shooting plan. This algorithm establishes a correspondence between depth and color information, enabling the generation of stitching views under any given view parameter. Furthermore, the algorithm is accelerated using GPU processing, resulting in a significant reduction in stitching time. The algorithm is successfully applied to generate selfie images for the Chang’e-5 mission.