906 research outputs found
Visual-UWB Navigation System for Unknown Environments
Navigation applications relying on the Global Navigation Satellite System
(GNSS) are limited in indoor environments and GNSS-denied outdoor terrains such
as dense urban or forests. In this paper, we present a novel accurate, robust
and low-cost GNSS-independent navigation system, which is composed of a
monocular camera and Ultra-wideband (UWB) transceivers. Visual techniques have
gained excellent results when computing the incremental motion of the sensor,
and UWB methods have proved to provide promising localization accuracy due to
the high time resolution of the UWB ranging signals. However, the monocular
visual techniques with scale ambiguity are not suitable for applications
requiring metric results, and UWB methods assume that the positions of the UWB
transceiver anchor are pre-calibrated and known, thus precluding their
application in unknown and challenging environments. To this end, we advocate
leveraging the monocular camera and UWB to create a map of visual features and
UWB anchors. We propose a visual-UWB Simultaneous Localization and Mapping
(SLAM) algorithm which tightly combines visual and UWB measurements to form a
joint non-linear optimization problem on Lie-Manifold. The 6 Degrees of Freedom
(DoF) state of the vehicles and the map are estimated by minimizing the UWB
ranging errors and landmark reprojection errors. Our navigation system starts
with an exploratory task which performs the real-time visual-UWB SLAM to obtain
the global map, then the navigation task by reusing this global map. The tasks
can be performed by different vehicles in terms of equipped sensors and payload
capability in a heterogeneous team. We validate our system on the public
datasets, achieving typical centimeter accuracy and 0.1% scale error.Comment: Proceedings of the 31st International Technical Meeting of the
Satellite Division of The Institute of Navigation (ION GNSS+ 2018
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