Isaac Gym achieves 2-3 orders of magnitude faster robot policy training by keeping physics simulation and PyTorch-based RL entirely on GPU with direct buffer sharing.
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A literature review of pHHI that proposes a taxonomy of interaction types by modality and engagement level while outlining pathways to integrate control, intent, and modeling for more seamless humanoid-human collaboration.
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Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning
Isaac Gym achieves 2-3 orders of magnitude faster robot policy training by keeping physics simulation and PyTorch-based RL entirely on GPU with direct buffer sharing.
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Toward Seamless Physical Human-Humanoid Interaction: Insights from Control, Intent, and Modeling with a Vision for What Comes Next
A literature review of pHHI that proposes a taxonomy of interaction types by modality and engagement level while outlining pathways to integrate control, intent, and modeling for more seamless humanoid-human collaboration.