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.
xvio: A range-visual- inertial odometry framework,
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
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.
citing papers explorer
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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.