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Relative navigation of autonomous GPS-degraded micro air vehicles

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Abstract

Unlike many current navigation approaches for micro air vehicles, the relative navigation (RN) framework presented in this paper ensures that the filter state remains observable in GPS-denied environments by working with respect to a local reference frame. By subtly restructuring the problem, RN ensures that the filter uncertainty remains bounded, consistent, and normally-distributed, and insulates flight-critical estimation and control processes from large global updates. This paper thoroughly outlines the RN framework and demonstrates its practicality with several long flight tests in unknown GPS-denied and GPS-degraded environments. The relative front end is shown to produce low-drift estimates and smooth, stable control while leveraging off-the-shelf algorithms. The system runs in real time with onboard processing, fuses a variety of vision sensors, and works indoors and outdoors without requiring special tuning for particular sensors or environments. RN is shown to produce globally-consistent, metric, and localized maps by incorporating loop closures and intermittent GPS measurements.

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Notes

  1. The PX4 firmware is customized to accept inputs from the onboard computer while also allowing an RC safety pilot to override these commands if necessary. We have subsequently transitioned to using the ROSflight autopilot (Jackson et al. 2016a); see https://rosflight.org.

  2. Individual edge covariances can also be combined using the fourth-order analytical approximation presented by Barfoot and Furgale (2014).

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Acknowledgements

This work has been funded by the Center for Unmanned Aircraft Systems (C-UAS), a National Science Foundation Industry/University Cooperative Research Center (I/UCRC) under NSF award Numbers IIP-1161036 and CNS-1650547, along with significant contributions from C-UAS industry members. This work was also supported in part by Air Force Research Laboratory Science and Technology (AFRL S&T) sponsorship. This research was conducted with Government support under and awarded by DoD, Air Force Office of Scientific Research, National Defense Science and Engineering Graduate (NDSEG) Fellowship, 32 CFR 168a. The authors would like to thank Kevin Brink of the Air Force Research Laboratory Munitions Directorate (AFRL/RW) for his support of this project and for his valuable insights.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT, 84602, USA

    David O. Wheeler & Randal W. Beard

  2. Department of Mechanical Engineering, Brigham Young University, Provo, UT, 84602, USA

    Daniel P. Koch, James S. Jackson, Gary J. Ellingson, Paul W. Nyholm & Timothy W. McLain

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  1. David O. Wheeler
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Wheeler, D.O., Koch, D.P., Jackson, J.S. et al. Relative navigation of autonomous GPS-degraded micro air vehicles. Auton Robot 44, 811–830 (2020). https://doi.org/10.1007/s10514-019-09899-4

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