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A survey reviews three roles of 3D generation in embodied intelligence and robot simulation
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Tianwei Ye and other authors published a survey that categorizes the uses of 3D generation in embodied intelligence and robot simulation into three types: generating simulation-ready assets with articulated structure, physical properties, and deformable content; building interactive, task-oriented simulation scenes; and serving as a sim-to-real bridge, supporting digital twin reconstruction, data augmentation, and synthetic demonstrations. The authors state that the field is shifting from pursuing visual realism toward interaction usability, and they list major bottlenecks such as limited physical annotation, the disconnect between geometric quality and physical validity, fragmented evaluation, and the sim-to-real gap.
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- Survey: 3D Generation for Embodied AI and Robotic Simulation
This survey examines three roles of 3D generation in embodied AI and robotic simulation: as a data generator producing simulation-ready assets with articulated structure, physical properties, and deformable content; as a builder of interactive, task-oriented scenes for simulation environments; and as a sim-to-real bridge supporting digital twin reconstruction, data augmentation, and synthetic demonstrations. The authors note that the field is shifting from visual realism toward interactive usability, and they list key bottlenecks including limited physical annotation, the disconnect between geometric quality and physical validity, fragmented evaluation, and the sim-to-real gap.
arXiv cs.RO ·