TY - GEN
T1 - Guided exploration for coordinated autonomous soaring flight
AU - Cheng, Kwok
AU - Langelaany, Jack W.
N1 - Funding Information:
This research was funded by the Office of Naval Research under Grant N000141110656. The Arduino autopilot (The Raptor) was developed by Nathan Depenbusch and Shawn Daugherty from the Air Vehicle Intelligence and Autonomy Laboratory (AVIA).
PY - 2014
Y1 - 2014
N2 - An approach to guide cooperative wind field mapping for autonomous soaring is presented. The environment is discretized into a grid and a Kalman filter is used to estimate vertical wind speed in each cell. Exploration is driven by uncertainty in the vertical wind speed estimate and by the relative likelihood that a thermal will occur in a given cell. This relative likelihood is computed based on solar incidence, computed from a digital elevation map of terrain (obtained from US Geological Survey) and the position of the sun. An exploration priority function is computed for each cell, and mapping is guided by this exploration priority. The effectiveness of this approach is evaluated by using Monte Carlo simulation with different flock sizes, topographic elevation models and different level of altitude floors that triggers immediate energy exploitation mode. Simulation result indicates an overall improvement in endurance while priori information is precise. With high uncertainty in thermal distribution, a high altitude floor prevents performance loss in guided exploration. Final simulation result obtained using a commercially available high fidelity simulator demonstrates feasibility of the cooperative mapping and guided exploration approach.
AB - An approach to guide cooperative wind field mapping for autonomous soaring is presented. The environment is discretized into a grid and a Kalman filter is used to estimate vertical wind speed in each cell. Exploration is driven by uncertainty in the vertical wind speed estimate and by the relative likelihood that a thermal will occur in a given cell. This relative likelihood is computed based on solar incidence, computed from a digital elevation map of terrain (obtained from US Geological Survey) and the position of the sun. An exploration priority function is computed for each cell, and mapping is guided by this exploration priority. The effectiveness of this approach is evaluated by using Monte Carlo simulation with different flock sizes, topographic elevation models and different level of altitude floors that triggers immediate energy exploitation mode. Simulation result indicates an overall improvement in endurance while priori information is precise. With high uncertainty in thermal distribution, a high altitude floor prevents performance loss in guided exploration. Final simulation result obtained using a commercially available high fidelity simulator demonstrates feasibility of the cooperative mapping and guided exploration approach.
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U2 - 10.2514/6.2014-0969
DO - 10.2514/6.2014-0969
M3 - Conference contribution
AN - SCOPUS:84894432811
SN - 9781600869624
T3 - AIAA Guidance, Navigation, and Control Conference
BT - AIAA Guidance, Navigation, and Control Conference
T2 - AIAA Guidance, Navigation, and Control Conference 2014 - SciTech Forum and Exposition 2014
Y2 - 13 January 2014 through 17 January 2014
ER -