Robotics: Science and Systems XIV

Autonomous Thermalling as a Partially Observable Markov Decision Process

Iain Guilliard, Rick Rogahn, Jim Piavis, Andrey Kolobov

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.

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Bibtex:

  
@INPROCEEDINGS{Guilliard-RSS-18, 
    AUTHOR    = {Iain Guilliard AND Rick Rogahn AND Jim Piavis AND Andrey Kolobov}, 
    TITLE     = {Autonomous Thermalling as a Partially Observable Markov Decision Process}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2018}, 
    ADDRESS   = {Pittsburgh, Pennsylvania}, 
    MONTH     = {June}, 
    DOI       = {10.15607/RSS.2018.XIV.068} 
}