Abstract: Abstract: For extraterrestrial exploration missions such as Mars sample return, high-precision and continuously updatable modeling of the sampling site terrain is a critical foundation for autonomous sampling decision-making and operational safety. Existing terrain reconstruction methods mainly rely on stereo vision, which is constrained by limited field of view and baseline configuration, making it difficult to cover the large operational workspace of a sampling manipulator. Although monocular arm-mounted cameras provide flexible viewpoints, they suffer from scale ambiguity and geometric inconsistency. To address these limitations, this study investigates terrain reconstruction under heterogeneous camera collaboration. A multi-camera system composed of a stereo camera and a heterogeneous monocular camera is constructed. Stereo vision is first employed to obtain an initial terrain model with true metric scale. The pose of the heterogeneous camera is then estimated through geometric relationship modeling, enabling the transfer of stereo depth information into the monocular view. By enforcing scale and geometric alignment on the monocular reconstruction, incremental fusion and updating relative to the stereo point cloud are achieved. Experimental results demonstrate that the proposed method effectively extends the spatial coverage of terrain reconstruction while preserving scale consistency and geometric stability, significantly improving modeling completeness in complex operational regions. The approach provides reliable geometric support for terrain understanding and operational assessment in Mars sample collection missions.

Key words: Heterogeneous Images, Stereo reconstruction, Monocular depth estimation, Depth Registration, Incremental 3D reconstruction