Abstract
In this paper, we present our experience in building a mobile imaging system that incorporates multi-modality sensors for road surface mapping and inspection applications. Our proposed system leverages 3D laser-range sensors, video cameras, global positioning systems (GPS) and inertial measurement units (IMU) towards the generation of photo-realistic, geometrically accurate, geo-referenced 3D models of road surfaces. Based on our summary of the state-of-the-art systems for a road distress survey, we identify several challenges in the real-time deployment, integration and visualization of the multi-sensor data. Then, we present our data acquisition and processing algorithms as a novel two-stage automation procedure that can meet the accuracy requirements with real-time performance. We provide algorithms for 3D surface reconstruction to process the raw data and deliver detail preserving 3D models that possess accurate depth information for characterization and visualization of cracks as a significant improvement over contemporary commercial video-based vision systems.
| Original language | English |
|---|---|
| Pages (from-to) | 808-818 |
| Number of pages | 11 |
| Journal | Optics and Lasers in Engineering |
| Volume | 45 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jul 2007 |
| Externally published | Yes |
Funding
This work was supported by the DOE University Research Program in Robotics under Grant DOE-DEFG02-86NE37968 and by the DOD/RDECOM/NAC/ARC Program, R01-1344-18. The authors would also like to thank Doug Warren for helping with the instrumentation of our mobile mapping system.
Keywords
- 3D geometric mapping
- Laser range scanning
- Multi-sensor integration
- Road surface reconstruction