Recent studies have demonstrated that images constructed from lidar reflectance information exhibit superior robustness to lighting changes. However, due to the scanning nature of the lidar and assumptions made in previous implementations, data acquired during continuous vehicle motion suffer from geometric motion distortion and can subsequently result in poor metric visual odometry (VO) estimates, even over short distances (e.g., 5-10 m). The first part of this thesis revisits the measurement timing assumption made in previous systems, and proposes a frame-to-frame VO estimation framework based on a pose-interpolation scheme that explicitly accounts for the exact acquisition time of each intrinsic, geometric feature measurement. The second part of this thesis investigates a novel method of lidar calibration that can be applied without consideration of the internal structure of the sensor. Both methods are validated using experimental data collected from a planetary analogue environment with a real scanning laser rangefinder.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/42820 |
| Date | 22 November 2013 |
| Creators | Dong, Hang |
| Contributors | Barfoot, Timothy D. |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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