Name
Abstract | ||
|---|---|---|
Unmanned Aerial Vehicles (UAV)s can control their altitude and orientation using the horizon as a reference. Typically this task is performed via edge-detection vision processing techniques implemented in a computer or digital electronics. We demonstrate a proof-of-principle for a memristive cellular automata (CA) system which can simply interface with an analog electronic control system. Our aim is a cheaper, lighter and more robust low-level system. Low-quality, noisy and wide-angle images consistent with cheap cameras have been tested and, even with these issues, the system can recognise the tilt angle and express it as relative activation of cells at the edge of a CA which could be used to drive motors to right the aircraft. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-662-43645-5_9 | Lecture Notes in Artificial Intelligence |
Keywords | Field | DocType |
Cellular automata,Memristors,Image processing,UAV | Computer vision,Cellular automaton,Digital electronics,Vision processing,Memristor,Visual processing,Electronic control system,Computer science,Horizon,Image processing,Artificial intelligence | Conference |
Volume | ISSN | Citations |
8069 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ioannis Georgilas | 1 | 18 | 3.59 |
| Ella Gale | 2 | 79 | 12.05 |
| andrew adamatzky | 3 | 1180 | 163.89 |
| Chris Melhuish | 4 | 747 | 87.61 |