Planetary Terrain Classification is a computational method in planetary robotics that categorizes surface regions of celestial bodies based on distinctive morphological, compositional, and topographical features derived from remote sensing data.
49
Publications
2.3K
Citations
164
Authors
61
Institutions
Publications per year
2017–2026
16
Parents
Publications
49
SPOC: Deep Learning-based Terrain Classification for Mars Rover Missions
Brandon Rothrock, Ryan Kennedy, Chris Cunningham et al. · AIAA SPACE 2016 · 2016 · 159 citations
1–5 of 49
Authors
164
- MO
6
h-index
- KI
5
h-index
- TF
4
h-index
- LB
3
h-index
- WD
2
h-index
1–5 of 164
Institutions
61
Jet Propulsion Laboratory
Pasadena, United States
10 h-index
38 publications
2.8K citations
Massachusetts Institute of Technology
Cambridge, United States
7 h-index
18 publications
1.5K citations
Lunar and Planetary Institute
Houston, United States
4 h-index
6 publications
154 citations
California Institute of Technology
Pasadena, United States
2 h-index
3 publications
106 citations
University of Massachusetts Boston
Boston, United States
2 h-index
3 publications
167 citations
University of Houston
Houston, United States
2 h-index
2 publications
92 citations
University of Vermont
Burlington, United States
2 h-index
7 publications
351 citations
Instituto Superior Técnico
Lisbon, Portugal
2 h-index
2 publications
92 citations
1–8 of 61
Venues
- Icarus
4 publications · 105 citations
4
h-index
- Journal of Geophysical Research Atmospheres
JGR · 2 publications · 45 citations
2
h-index
- Journal of Field Robotics
JFR · 2 publications · 164 citations
2
h-index
- Robotica
2 publications · 53 citations
2
h-index
- Planetary and Space Science
2 publications · 48 citations
2
h-index
1–5