Name
Abstract | ||
|---|---|---|
Understanding the environment is a key requirement for any autonomous robot operation. There is extensive research on mapping geometric structure and perceiving objects. However, the environment is also defined by the movement patterns in it. Information about human motion patterns can, e.g., lead to safer and socially more acceptable robot trajectories. Airflow pattern information allow to plan e... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/LRA.2017.2660060 | IEEE Robotics and Automation Letters |
Keywords | Field | DocType |
Trajectory,Robots,Atmospheric modeling,Planning,Gaussian distribution,Probabilistic logic,Gaussian mixture model | Observable,Flow (psychology),Artificial intelligence,Engineering,Autonomous robot,Mobile robot,Robotics,Distributed computing | Journal |
Volume | Issue | ISSN |
2 | 2 | 2377-3766 |
Citations | PageRank | References |
5 | 0.48 | 13 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tomasz Kucner | 1 | 64 | 7.84 |
| Martin Magnusson | 2 | 71 | 10.10 |
| Erik Schaffernicht | 3 | 66 | 8.54 |
| Victor Manuel Hernandez Bennetts | 4 | 74 | 7.30 |
| Achim J. Lilienthal | 5 | 1468 | 113.18 |