Efficient Large‐scale Three‐dimensional Mobile Mapping for Underground Mines

Abstract

Mapping large-scale underground environments, such as mines and tunnels, is typically a time-consuming and challenging endeavor. Existing methods based on terrestrial laser scanning are inefficient, and commercial mobile mapping systems are not suitable for underground use. Simultaneous Localization and Mapping (SLAM) solutions have the potential to efficiently survey underground environments while continuously moving, without relying on external positioning systems. However, no three-dimensional (3D) SLAM systems have thus far been demonstrated to be capable of mapping underground mines at kilometer scales. We have developed a solution that can accurately estimate, based on laser range and inertial measurements, the six-degrees-offreedom trajectory of a sensor platform that continuously moves through an environment, as well as a 3D point cloud map of that environment. The key software components of the solution are continuous-time non-rigid registration, scalable place recognition, and robust pose graph optimization. A system consisting of a spinning 2D laser scanner and an industrial-grade inertial measurement unit mounted on a light vehicle was deployed at Northparkes Mine in Australia and used to map over 17 km of mine tunnel in 113 min while traveling at typical mine traffic speeds. Our processing software automatically produces a trajectory and point cloud of the mine in under half of the data acquisition time. The accuracy of the solution exceeds the raw sensor characteristics and matches closely to a surveyed map of the same environment. C 2014 Wiley Periodicals, Inc.

Field Navigation Using Fuzzy Elevation Maps Built with Local 3D Laser Scans

“…In past years, 3D data acquisition from UGVs was usually performed in a stop-and-go manner [10,11], but, nowadays, it can be performed in motion by using some kind of simultaneous localization and mapping (SLAM) by combining data from odometry [12] or from an inertial unit [13].…”

Design of a Mobile Robot for Air Ducts Exploration

“…While [11] analyzes recent advances in both domains, [12] presents a localization approach based on a strap-down Inertial Measurement Unit (IMU). In terms of navigation challenges, [13] provides a method to detect the walls in a corridor to enable an efficient navigation of a mobile robot, and [14] focuses on the mapping of large-scale underground environments. The present work focuses instead on ventilation ducts, which typically have a relatively small scale.…”

Multi-Sensor As-Built Models of Complex Industrial Architectures

“…Regarding 3D georeferenced point cloud acquisition, some noticeable improvements have come from robotic and computer vision research programs on fast 3D scanning indoors, such as range sensors [5], backpack scanning systems [6], handheld [7] or mounted on mobile platforms in various shapes and sizes [8,9]. However, these systems, either for local precision [5][6][7] or global georeferencing errors [9], deal mostly with decimeter accuracy.…”

“…However, these systems, either for local precision [5][6][7] or global georeferencing errors [9], deal mostly with decimeter accuracy. Moreover, many indoor localization and mapping systems require planar objects and/or straight corridors to reduce drift using elaborate algorithms, such as "iterate closest point + inertial measurement unit + planar" proposed in [6].…”