Autonomous Thermalling as a Partially Observable Markov Decision Process (Extended Version)
Robotics
2018-05-28 v1 Systems and Control
Abstract
Small uninhabited aerial vehicles (sUAVs) commonly rely on active propulsion to stay airborne, which limits flight time and range. To address this, autonomous soaring seeks to utilize free atmospheric energy in the form of updrafts (thermals). However, their irregular nature at low altitudes makes them hard to exploit for existing methods. We model autonomous thermalling as a POMDP and present a receding-horizon controller based on it. We implement it as part of ArduPlane, a popular open-source autopilot, and compare it to an existing alternative in a series of live flight tests involving two sUAVs thermalling simultaneously, with our POMDP-based controller showing a significant advantage.
Cite
@article{arxiv.1805.09875,
title = {Autonomous Thermalling as a Partially Observable Markov Decision Process (Extended Version)},
author = {Iain Guilliard and Richard Rogahn and Jim Piavis and Andrey Kolobov},
journal= {arXiv preprint arXiv:1805.09875},
year = {2018}
}