Name
Title | ||
|---|---|---|
Vision-Based Estimation of Driving Energy for Planetary Rovers Using Deep Learning and Terramechanics. |
Abstract | ||
|---|---|---|
This letter presents a prediction algorithm of driving energy for future Mars rover missions. The majority of future Mars rovers would be solar-powered, which would require energy-optimal driving to maximize the range with limited energy. The essential and arguably the most challenging technology for realizing energy-optimal driving is the capability to predict the driving energy, which is needed ... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LRA.2019.2928765 | IEEE Robotics and Automation Letters |
Keywords | Field | DocType |
Space exploration,Energy consumption,Space vehicles,Mobile robots,Deep learning | Motion planning,Mars Exploration Program,Terrain,Network architecture,Real-time computing,Control engineering,Artificial intelligence,Engineering,Deep learning,Terramechanics,Mars rover,Energy consumption | Journal |
Volume | Issue | ISSN |
4 | 4 | 2377-3766 |
Citations | PageRank | References |
2 | 0.37 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shoya Higa | 1 | 2 | 0.70 |
| Yumi Iwashita | 2 | 212 | 23.59 |
| Kyohei Otsu | 3 | 7 | 3.51 |
| Masahiro Ono | 4 | 133 | 14.40 |
| Olivier Lamarre | 5 | 2 | 0.37 |
| Annie Didier | 6 | 2 | 0.37 |
| Mark Hoffmann | 7 | 2 | 0.37 |