NVIDIA Introduces ADEPT: Zero-Shot Real-World Transfer of Sim-Trained Visuo-Tactile Policies
dr_alphalyrae · x · 2026-09-01
NVIDIA, in collaboration with SharpaRobotics, introduces ADEPT, a pre-training and post-training paradigm that uses RL entirely in simulation to train visuo-tactile policies, followed by zero-shot deployment in the real world. The research utilizes IsaacLab to simulate five tactile sensors at the fingertips and successfully transfers policies to two different arm-hand combinations without tuning any RL hyperparameters or reward functions.
More from Embodied
- Opus-assisted open design: a $31k low-field head MRI sketched in hours — DreamFly_13 · 2026-10-18
- DIY robotics build: servo mechanism tested, wide yaw range but limited pitch — _Stocko_ · 2026-10-18
- Brain implants are restoring speech to people with ALS, Science reports — EricMTrautmann · 2026-10-18
- Meta wearables VP runs his AI agent across 3 phones and 23 pairs of glasses — nikola_mr64990 · 2026-10-18
- DeepSeek reportedly invests in embodied AI startups, in talks with robot founders — 量子位 · 2026-10-18
- AMI-EV: spinning prism gives event cameras stable texture, Science Robotics 2024 — RexDouglass · 2026-10-18