CLASP achieves 87% success in open-vocabulary desktop grasping via dual-pathway perception, asynchronous closed-loop evaluation, and automated multimodal data synthesis.
Open x-embodiment: Robotic learning datasets and rt-x models
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V-CAGE automates the creation of scalable, high-quality robotic manipulation datasets through context-aware scene construction, closed-loop visual verification, and perceptually-driven compression.
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CLASP: Closed-loop Asynchronous Spatial Perception for Open-vocabulary Desktop Object Grasping
CLASP achieves 87% success in open-vocabulary desktop grasping via dual-pathway perception, asynchronous closed-loop evaluation, and automated multimodal data synthesis.
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V-CAGE: Vision-Closed-Loop Agentic Generation Engine for Robotic Manipulation
V-CAGE automates the creation of scalable, high-quality robotic manipulation datasets through context-aware scene construction, closed-loop visual verification, and perceptually-driven compression.