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EnglishIn many unmanned aerial vehicle (UAV) applications, flexible trajectory generation algorithms are required to enable high levels of autonomy for critical mission phases, such as take-off, area coverage, and landing. In this paper, we present a guidance approach which uses the improved intrinsic tau guidance theory to create 4-D trajectories for the desired time-to-contact (TTC) with a landing platform tracked by a visual sensor. This allows us to perform maneuvers with tunable trajectory profiles, while catering for static or non-static starting and terminating motion states. We validate our method using a rotary-wing UAV to land on a static platform.Results from simulations and outdoor experiments show that our approach achieves smooth, accurate landings with easily adjustable parameters.
| Titolo: | Improved Tau-Guidance and Vision-aided Navigation for Robust Autonomous Landing of UAVs | |
| Autori: | ||
| Data di pubblicazione: | 2017 | |
| Abstract: | In many unmanned aerial vehicle (UAV) applications, flexible trajectory generation algorithms are required to enable high levels of autonomy for critical mission phases, such as take-off, area coverage, and landing. In this paper, we present a guidance approach which uses the improved intrinsic tau guidance theory to create 4-D trajectories for the desired time-to-contact (TTC) with a landing platform tracked by a visual sensor. This allows us to perform maneuvers with tunable trajectory profiles, while catering for static or non-static starting and terminating motion states. We validate our method using a rotary-wing UAV to land on a static platform.Results from simulations and outdoor experiments show that our approach achieves smooth, accurate landings with easily adjustable parameters. | |
| Handle: | http://hdl.handle.net/11588/687642 | |
| Appare nelle tipologie: | 4.1 Articoli in Atti di convegno |
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