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- Title
On registration methods for SLAM with low resolution LiDAR sensor.
- Authors
Aguilar-Moreno, Marina; Graña, Manuel
- Abstract
Affordable light detection and ranging sensors are becoming available for tasks such as simultaneous localization and mapping (SLAM) in robotics and autonomous driving; however, these sensors offer less quality data of lower resolution that hinders the performance of registration methods. The deep learning based approaches seem to be sensitive to these data flaws. Specifically, a state-of-the-art deep learning-based approach failed to produce meaningful results after several attempts to carry out transfer learning over a dataset collected indoors with one such affordable sensors. The paper introduces a hybrid approach combining two well-established registration techniques, the iterative closest point algorithm and the normal distributions transform that achieves good performance on the SLAM task over the same dataset.
- Subjects
OPTICAL radar; LIDAR; DEEP learning; DETECTORS; RECORDING &; registration; GAUSSIAN distribution
- Publication
Logic Journal of the IGPL, 2023, Vol 31, Issue 4, p751
- ISSN
1367-0751
- Publication type
Article
- DOI
10.1093/jigpal/jzac037