Name
Abstract | ||
|---|---|---|
Environment monitoring remains a major challenge for mobile robots, especially in densely cluttered or highly populated dynamic environments, where uncertainties originated from environment and sensor significantly challenge the robot's perception. This paper proposes an effective occupancy filtering method called the dual probability hypothesis density (DPHD) filter, which models uncertain phenom... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TITS.2017.2770152 | IEEE Transactions on Intelligent Transportation Systems |
Keywords | Field | DocType |
Vehicle dynamics,Uncertainty,Computational modeling,Monitoring,Adaptation models,Bayes methods,Radio frequency | Computer vision,Phase space,Particle filter,Algorithm,Filter (signal processing),Vehicle dynamics,Artificial intelligence,Engineering,Robot,State space,Mobile robot,Bayesian probability | Journal |
Volume | Issue | ISSN |
19 | 9 | 1524-9050 |
Citations | PageRank | References |
1 | 0.37 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongqi Fan | 1 | 32 | 11.25 |
| Tomasz Kucner | 2 | 64 | 7.84 |
| Martin Magnusson | 3 | 71 | 10.10 |
| Tiancheng Li | 4 | 96 | 8.40 |
| Achim J. Lilienthal | 5 | 1468 | 113.18 |