Project Frigatebird is aimed at enabling small fixed-wing UAVs to travel long distances by soaring -- taking advantage of rising air regions the way human sailplane pilots and bird species like frigatebirds do -- using AI planning and learning techniques.
Currenty, this repository contains an implementation of POMDSoar, an algorithm that allows a sailplane UAV to detect and gain altitude in thermals, "columns" of rising air that occur over certain regions of Earth's surface. This approach, based on solving a Partially Observable Markov Decision Process, is described in
I. Guilliard, R. Rogahn, J. Piavis, A. Kolobov. "Autonomous Thermalling as a Partially Observable Markov Decision Process." Robotics: Science and Systems conference, 2018. https://arxiv.org/pdf/1805.09875.pdf
We implemented POMDSoar as a soaring controller integrated into a fork of ArduPlane, the fixed-wing flavor of ArduPilot open-source drone autopilot suite (original ArduPlane code, wiki). The code in the Frigatebird repository allows building this modified version of ArduPlane. Please see BUILD.md for building instructions.
The DATA subdirectory contains ArduPlane parameter files and an example geofenced waypoint course for running POMDSoar on a Radian Pro sUAV as in the experiments in the above paper.
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Github repository: https://github.com/Microsoft/Frigatebird
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The main site (http://ardupilot.org), developer wiki (http://dev.ardupilot.org), and discussion page (http://discuss.ardupilot.org) of the parent project, ArduPilot, is useful for understanding how to modify Frigatebird.
Project Frigatebird is licensed under the GNU General Public License, version 3
- Iain Guilliard, main developer of Frigatebird's POMDSoar thermalling controller
- Andrey Kolobov, project lead
We would like to say a big "thank you!" to the developer community of ArduPilot. Their code and advice has greatly helped in starting Project Frigatebird.