Introduces a 2.7M-label benchmark for grasp feasibility from point clouds and shows a point-cloud transformer reaching 0.996 AUROC on novel objects while running faster than sampling planners.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Presents a verification-gated agentic mission-state governance framework using synchronized task forests and blackboards with deterministic verification before any state commits in multi-robot systems.
citing papers explorer
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Learning Motion Feasibility from Point Clouds in Cluttered Environments
Introduces a 2.7M-label benchmark for grasp feasibility from point clouds and shows a point-cloud transformer reaching 0.996 AUROC on novel objects while running faster than sampling planners.
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Verification-Gated Agentic Mission-State Governance for Intelligent Industrial Multi-Robot Systems
Presents a verification-gated agentic mission-state governance framework using synchronized task forests and blackboards with deterministic verification before any state commits in multi-robot systems.