A terrain-adaptive epsilon-constraint MPC with semi-parametric SGP vehicle-terrain model achieves 94% success rate, 24% lower orientation deviation, and 23% better trade-off quality than MPPI and GAKD baselines.
ACM Transactions on Graphics (TOG)39(6), 1–15 (2020)
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A neural network trained on full-reference perceptual quality labels predicts minimal sufficient resolution for rendered video to enable power-efficient client-side rendering.
A co-design framework learns task-specific hand shapes and complementary control policies, supporting design, training, fabrication, and deployment of new dexterous hands in under 24 hours.
Implicit neural fields enable joint optimization of manufacturing layers and toolpaths with explicit collision avoidance in a single differentiable pipeline for multi-axis processes.
citing papers explorer
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A Terrain-Adaptive epsilon-Constraint MPC for Uneven Terrain Kinodynamic Planning
A terrain-adaptive epsilon-constraint MPC with semi-parametric SGP vehicle-terrain model achieves 94% success rate, 24% lower orientation deviation, and 23% better trade-off quality than MPPI and GAKD baselines.
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Seeing enough: non-reference perceptual resolution selection for power-efficient client-side rendering
A neural network trained on full-reference perceptual quality labels predicts minimal sufficient resolution for rendered video to enable power-efficient client-side rendering.
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House of Dextra: Cross-embodied Co-design for Dexterous Hands
A co-design framework learns task-specific hand shapes and complementary control policies, supporting design, training, fabrication, and deployment of new dexterous hands in under 24 hours.
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Implicit Neural Field-Based Process Planning for Multi-Axis Manufacturing: Direct Control over Collision Avoidance and Toolpath Geometry
Implicit neural fields enable joint optimization of manufacturing layers and toolpaths with explicit collision avoidance in a single differentiable pipeline for multi-axis processes.