Motion-aware Traversability (MAT) models each terrain region as a Gaussian function of velocity, enabling robots to predict and use speed-dependent costs for agile jumping in off-road navigation.
Learning-on-the-drive: Self-supervised adap- tive long-range perception for high-speed offroad driving
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
A physically viable world model augments 3D Gaussian splats with physics simulation to assess robot route feasibility under simulated terrain changes like flooding, revealing failures not visible in static maps.
citing papers explorer
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Learning When to Jump for Off-road Navigation
Motion-aware Traversability (MAT) models each terrain region as a Gaussian function of velocity, enabling robots to predict and use speed-dependent costs for agile jumping in off-road navigation.
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Path Planning in Physically Viable World Models
A physically viable world model augments 3D Gaussian splats with physics simulation to assess robot route feasibility under simulated terrain changes like flooding, revealing failures not visible in static maps.