Name
Abstract | ||
|---|---|---|
This paper targets the problem of generating a trajectory free of collisions for autonomous drones evolving in 3D static environments. To solve this problem, the work is focused on extending the classical 2D rectangular cell decomposition towards a 3D rectangular cuboid representation of the free space. The new approach is compared to a rapidly-exploring random tree method for the same scenario. Testing and evaluation through numerical simulation prove the effectiveness of the proposed path planning approach. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICSTCC.2019.8886091 | 2019 23rd International Conference on System Theory, Control and Computing (ICSTCC) |
Keywords | Field | DocType |
path planning,cell decomposition,rapidly-exploring random tree | Motion planning,Random tree,Computer simulation,Control theory,Computer science,Algorithm,Free space,Cuboid,Drone,Robot,Trajectory | Conference |
ISSN | ISBN | Citations |
2372-1618 | 978-1-7281-0700-4 | 1 |
PageRank | References | Authors |
0.38 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marian Lupascu | 1 | 1 | 0.38 |
| Sofia Hustiu | 2 | 1 | 0.38 |
| Adrian Burlacu | 3 | 6 | 3.59 |
| Marius Kloetzer | 4 | 476 | 29.21 |