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This paper introduces an innovative approach to 3D environmental mapping through the integration of a compact, handheld sensor package with a two-stage sensor fusion pipeline. The sensor package, incorporating LiDAR, IMU, RGB, and thermal cameras, enables comprehensive and robust 3D mapping of various environments. By leveraging Simultaneous Localization and Mapping (SLAM) and thermal imaging, our solution offers good performance in conditions where global positioning is unavailable and in visually degraded environments. The sensor package runs a real-time LiDAR-Inertial SLAM algorithm, generating a dense point cloud map that accurately reconstructs the geometric features of the environment. Following the acquisition of that point cloud, we post-process these data by fusing them with images from the RGB and thermal cameras and produce a detailed, color-enriched 3D map that is useful and adaptable to different mission requirements. We demonstrated our system in a variety of scenarios, from indoor to outdoor conditions, and the results showcased the effectiveness and applicability of our sensor package and fusion pipeline. This system can be applied in a wide range of applications, ranging from autonomous navigation to smart agriculture, and has the potential to make a substantial benefit across diverse fields.
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This content will become publicly available on May 19, 2026
Heterogeneous Sensor Fusion and Active Perception for Transparent Object Reconstruction with a PDM2 Sensor and a Camera
- Award ID(s):
- 1925037
- PAR ID:
- 10580169
- Publisher / Repository:
- IEEE international Conference on Robotics and Automation (ICRA)
- Date Published:
- Format(s):
- Medium: X
- Location:
- Atlanta, GA
- Sponsoring Org:
- National Science Foundation
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