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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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GPS-Denied State Estimation for Blue/NDAA Unmanned Multi-Rotor Vehicles
Unmanned Aircraft Vehicle (UAV) state estimation and navigation in GPS-denied environments has received a great deal of attention, with several researchers exploring a variety of compensating estimation methods. These methods vary in capability, and usually trade off estimation accuracy for simplicity and fewer resource requirements. More advanced estimation schemes, while capable of providing good state estimates for longer periods of time, may not be suitable for small, limited resource vehicles such as UAVs. Simpler and less-accurate estimation methods, while less capable, are useful for introducing the topic to students as well as helping researchers establish flight capabilities, and may be more suitable on limited hardware. The Autonomous Vehicle Laboratory’s (AVL) REEF Estimator was designed to expedite the development of a group’s GPS-denied flight capabilities through its simple and modular design. This work seeks to extend the application of the REEF Estimator by adapting it to fit the Ardupilot flight stack so that the estimator may be used on a readily available and NDAA-compliant flight controller, specifically, a Pixhawk Cube Blue. In addition, the REEF Estimator has been containerized to further facilitate its deployment between different vehicle architectures with minimal need for reconfiguration or setup.
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- PAR ID:
- 10412535
- Publisher / Repository:
- American Institute of Aeronautics and Astronautics
- Date Published:
- Journal Name:
- AIAA SciTech 2023 Forum
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.2514/6.2023-2666
