Name
Abstract | ||
|---|---|---|
This article presents a software architecture for safe and reliable autonomous navigation of aerial robots in GPS-denied areas. The techniques employed within key modules from this architecture are explained in detail, such as a six-dimensional localization approach based on visual odometry and Monte Carlo localization, or a variant of the Lazy Theta* algorithm for motion planning. The aerial robot used to demonstrate this approach has been extensively tested over the past 2 years for localization and state estimation without any external positioning systems, autonomous local obstacle avoidance, and local path planning among other tasks. This article describes the architecture and main algorithms used to achieve these goals to build a robust autonomous system. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1002/rob.21757 | JOURNAL OF FIELD ROBOTICS |
Field | DocType | Volume |
Motion planning,Obstacle avoidance,Computer vision,Visual odometry,Simulation,Global Positioning System,Autonomous system (mathematics),Artificial intelligence,Software architecture,Engineering,Monte Carlo localization,Robot | Journal | 35.0 |
Issue | ISSN | Citations |
SP1.0 | 1556-4959 | 6 |
PageRank | References | Authors |
0.47 | 26 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francisco Javier Perez-Grau | 1 | 6 | 1.49 |
| Ricardo Ragel | 2 | 6 | 0.47 |
| Fernando Caballero | 3 | 610 | 45.38 |
| Antidio Viguria | 4 | 154 | 19.05 |
| Aníbal Ollero Baturone | 5 | 13 | 1.01 |