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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A Finite-Time Stable Observer for Relative Attitude Estimation
Relative motion estimation of one rigid body with respect to another is a problem that has immediate applications to formations and maneuvers involving multiple unmanned vehicles or collision avoidance between vehicles. A finite-time stable observer for relative attitude estimation of a rigid object using onboard sensors on an unmanned vehicle, is developed and presented here. This observer assumes sensor inputs from onboard vision and inertial sensors, with the vision sensors measuring at least three points on the object whose relative locations with respect to a body-fixed frame on the object are also assumed to be known. In the absence of any measurement noise, the estimated relative attitude is shown to converge to the actual relative pose in a finite-time stable manner. Numerical simulations indicate that this relative attitude observer is robust to persistent measurement errors and converges to a bounded neighborhood of the true attitude.
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- Award ID(s):
- 1739748
- NSF-PAR ID:
- 10195625
- Date Published:
- Journal Name:
- 2019 IEEE 58th Conference on Decision and Control (CDC)
- Page Range / eLocation ID:
- 7911 to 7916
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/CDC40024.2019.9029806
