xVIO: A Range-Visual-Inertial Odometry Framework
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xVIO is a range-visual-inertial odometry algorithm implemented at JPL. It has been demonstrated with closed-loop controls on-board unmanned rotorcraft equipped with off-the-shelf embedded computers and sensors. It can operate at daytime with visible-spectrum cameras, or at night time using thermal infrared cameras. This report is a complete technical description of xVIO. It includes an overview of the system architecture, the implementation of the navigation filter, along with the derivations of the Jacobian matrices which are not already published in the literature.
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Cited by 3 Pith papers
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Learning All-Terrain Locomotion for a Planetary Rover with Actively Articulated Suspension
A single RL policy trained in DARTS simulation on an actively suspended planetary rover enables autonomous traversal of rock fields, steps, sand ripples, and 20° sandy slopes with 37% lower cost of transport on dry sa...
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Learning All-Terrain Locomotion for a Planetary Rover with Actively Articulated Suspension
Reinforcement learning produces a single unified controller that lets an actively suspended planetary rover autonomously cross heterogeneous rough terrains after sim training and zero-shot hardware transfer.
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BEVIO: Efficient Bird's-Eye-View based Sparse-Update Visual-Inertial Odometry for Lunar Day-Night Navigation
BEVIO uses BEV-based image matching to enable reliable VIO at visual update rates as low as 0.25 Hz for lunar day-night rover navigation.
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