@inproceedings{564e7d4bb1d3429790dcac8244d8c808,
title = "Flight path planning for UAV atmospheric energy harvesting using heuristic search",
abstract = "This paper presents an approach to planning long distance autonomous soaring trajectories for small uninhabited aerial vehicles harvesting energy from the atmosphere. An A* algorithm is used with a cost function which is the weighted sum of energy required and distance to goal. The effect of varying the weight parameter on the ight paths is explored. The required initial energy for varying weight is examined, and the results are compared with a wavefront expansion planning algorithm. The weight is selected based on maximum energy utilization that is available from the atmosphere and minimizing time to reach the goal. Optimal weight is selected based on simulation results and the performance of A* is studied for a realistic wind field. Optimal energy efficient routes are predicted from a given wind field data.",
author = "Anjan Chakrabarty and Langelaany, {Jack W.}",
note = "Funding Information: This research was funded by the National Science Foundation under Grant IIS-0746655. The wind field data of Section V was provided by George S. Young, Brian J. Gaudet, Nelson L. Seaman and David R. Stauffer of the Penn State University Department of Meteorology.; AIAA Guidance, Navigation, and Control Conference ; Conference date: 02-08-2010 Through 05-08-2010",
year = "2010",
doi = "10.2514/6.2010-8033",
language = "English (US)",
isbn = "9781600869624",
series = "AIAA Guidance, Navigation, and Control Conference",
booktitle = "AIAA Guidance, Navigation, and Control Conference",
}