Combined Lidar and Sonar Mapping for Partially Submerged Infrastructure

Abstract

Advances in robotic mapping, planning, and perception have spurred applications-based robotics research in the domain of infrastructure inspection and preservation. Though a significant portion of this research has centered around the use of unmanned aerial, ground, and underwater vehicles, research in the use of unmanned surface vehicles (USVs) is limited. USVs present a unique opportunity to capture combined maps above and below water, which is essential for the inspection of waterspanning bridges, harbors, dams, and levees. In this paper, we investigate the use of USVs for infrastructure inspection by outfitting a USV platform with a multibeam sonar, horizontally and vertically mounted lidars, several ruggedized RGB cameras, and a high-rate inertial measurement unit (IMU). By time-synchronizing all sensors, we are able to fuse information collected from lidar, camera, and IMU units via tightly-coupled lidar-visual-inertial (LVI) simultaneous mapping and localization (SLAM). We validate our methodology by collecting sensory data of an abandoned quarry and by generating a combined 3D point cloud map using lidar data, multibeam sonar data, and maximum a posteriori trajectory from the LVI SLAM approach. Experiments validate the performance of the proposed USV system, highlighting challenges in extrinsic calibration of non-overlapping sensors, sonar denoising, and refined inter-keyframe pose estimation for key-frame based SLAM approaches.