Name
Abstract | ||
|---|---|---|
Glacial science could benefit tremendously from autonomous robots, but previous glacial robots have had perception issues in these colorless and featureless environments, specifically with visual feature extraction. This translates to failures in visual odometry and visual navigation. Glaciologists use near-infrared imagery to reveal the underlying heterogeneous spatial structure of snow and ice, ... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/LRA.2019.2959490 | IEEE Robotics and Automation Letters |
Keywords | DocType | Volume |
Feature extraction,Cameras,Ice,Snow,Visualization,Robots,Grain size | Journal | 5 |
Issue | ISSN | Citations |
2 | 2377-3766 | 0 |
PageRank | References | Authors |
0.34 | 7 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steven D. Morad | 1 | 0 | 0.34 |
| Jeremy Nash | 2 | 12 | 2.68 |
| Shoya Higa | 3 | 2 | 0.70 |
| Russell Smith | 4 | 0 | 0.34 |
| Aaron Parness | 5 | 68 | 12.26 |
| K. Barnard | 6 | 2564 | 269.41 |