4 papers · 1 filter
GPUSimBench: Towards Scalable and Reliable GPU-Accelerated Simulators in Embodied AI
Huzhenyu Zhang, Shenghai Yuan, Wenrui Yan +4
Data-driven embodied AI is rapidly transitioning into a paradigm that scales training through massively parallel simulation, where GPU-accelerated simulators serve as the foundatio…
SIM1: Physics-Aligned Simulator as Zero-Shot Data Scaler in Deformable Worlds
Yunsong Zhou, Hangxu Liu, Xuekun Jiang +12
Robotic manipulation with deformable objects represents a data-intensive regime in embodied learning, where shape, contact, and topology co-evolve in ways that far exceed the varia…
Nimbus: A Unified Embodied Synthetic Data Generation Framework
Zeyu He, Yuchang Zhang, Yuanzhen Zhou +10
Scaling data volume and diversity is critical for generalizing embodied intelligence. While synthetic data generation offers a scalable alternative to expensive physical data acqui…
LagMemo: Language 3D Gaussian Splatting Memory for Multi-modal Open-vocabulary Multi-goal Visual Navigation
Haotian Zhou, Xiaole Wang, He Li +5
Navigating to a designated goal using visual information is a fundamental capability for intelligent robots. To address the practical demands of multi-modal, open-vocabulary goal q…