Calibration of a multi-sensor wheeled robot for 3D mapping of underground mining tunnels

Mobile robotic systems show great potential for automation and a vast selection of tasks in everyday life and industrial facilities. The most important fields of application are related to limiting human exposure to harmful conditions and greatly increasing work safety, among other cost-driven factors. One of these field is the mining industry. While in surface mining automation of several tasks is already being done e.g., using drones, in GNSS-denied underground environments using such innovation at a market-ready level is significantly more challenging, also due to the difficulties of spatial data acquisition needed, e.g., for navigation. This paper presents a system calibration procedure (6D pose estimation) of a multi-sensor mobile robot developed for inspecting underground mining tunnels and infrastructures. We introduce the sensors setup for the acquisition of spatially-related data (images, laser scans) and propose a multi-step calibration workflow of the different perception devices, such as RGB, thermal cameras and LiDARs, in a coherent reference frame. The quality of subsequent calibration stages is investigated based on the visual results and derived statistical measures. The propose procedure allowed the relative pose estimation of all sensors without specialized setups and targets, utilizing only natural urban scenes and a standard checkerboard pattern.