Three-dimensional reconstruction in confined spaces is important for the manufacturing of aircraft wings, inspection of narrow pipes, examination of turbine blades, etc. It is also challenging because confined spaces tend to lack a positioning infrastructure, and conventional sensors often cannot detect objects in close range. Therefore, such tasks require a sensor that is compact, operates in short-range, and able to localize itself. In this paper, we introduce a miniature and low-cost 3D scanning system including an active laser-stripe triangulation hardware, integrated inertial sensors, and a Simultaneous Localization and Mapping (SLAM) software tailored for the sensor. The proposed system is capable of reconstructing photo-realistic 3D point cloud in real-time in spite of its compact monocular configuration. To achieve this capability, we propose an approach to capture both color and geometry using alternating shutter-speed on a single camera. A novel SLAM method is proposed to accurately localize the sensor by fusing laser, camera, and inertial measurements. Evaluation of localization accuracy and comparison on reconstruction performance against a significantly larger commercial off-the-shelf sensor demonstrate the proposed system’s advantages in real-world applications.
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Visual-Laser-Inertial SLAM Using a Compact 3D Scanner for Confined Space
Semantic Scholar · Engineering · 2021
Abstract
Three-dimensional reconstruction in confined spaces is important for the manufacturing of aircraft wings, inspection of narrow pipes, examination of turbine blades, etc. It is also challenging because confined spaces tend to lack a positioning infrastructure, and conventional sensors often cannot detect objects in close range. Therefore, such tasks require a sensor that is compact, operates in short-range, and able to localize itself. In this paper, we introduce a miniature and low-cost 3D scanning system including an active laser-stripe triangulation hardware, integrated inertial sensors, and a Simultaneous Localization and Mapping (SLAM) software tailored for the sensor. The proposed system is capable of reconstructing photo-realistic 3D point cloud in real-time in spite of its compact monocular configuration. To achieve this capability, we propose an approach to capture both color and geometry using alternating shutter-speed on a single camera. A novel SLAM method is proposed to accurately localize the sensor by fusing laser, camera, and inertial measurements. Evaluation of localization accuracy and comparison on reconstruction performance against a significantly larger commercial off-the-shelf sensor demonstrate the proposed system’s advantages in real-world applications.