ZHAO Xin, LIANG Fuxun, LI Jianping, Chen Yiping, Yang Bisheng
Lava tunnels widely exist on planets and satellites, which can provide natural shelter for humans to land on in the future. Research on lava tunnels is of great significance. However, there are many challenges in extraterrestrial lava tunnel detection. Existing terrestrial lava tunnel detection schemes have devices that are not portable, with low levels of automation and work efficiency, and cannot be directly applied to the detection of extraterrestrial lava tunnels. To address the above problems, this paper proposes a 3D detection method for extraterrestrial lava tunnels based on the lightweight mobile measurement system, achieving efficient and detailed mapping as well as 3D morphology of lava tunnels, and carries out the verification in Earth lava tunnels. First, laser scanning is used to obtain the point cloud in the lava tunnel efficiently, and the 3D point cloud map of the tunnel is generated based on the iterative Kalman filtering algorithm. Subsequently, through point cloud processing methods such as ground filtering, tunnel wall extraction, and normal vector estimation, the 3D reconstruction of lava tunnels is achieved, followed by morphological analysis. This paper selects the Xianren Cave and Qishier Cave in Haikou, Hainan Province, as simulation scenarios for extraterrestrial lava tunnels to conduct experiments. Experiments indicate that the proposed method realizes real-time autonomous 3D mapping of lava tunnels. The generated point cloud maps and 3D models are more accurate and contain more detailed terrain information compared to existing research results. These indicate the proposed method better meets the morphological analysis needs of lava tunnels and provides a foundation for the in-depth study of extraterrestrial lava tunnels.