Max Fu
@letian_fu • 1,525 subscribers
scaling robotics. prev @UCBerkeley @berkeley_ai @NVIDIA @Apple @autodesk
Videos
Robotics: coding agents’ next frontier. So how good are they? We introduce CaP-X: an open-source framework and benchmark for coding agents, where they write code for robot perception and control, execute it on sim and real robots, observe the outcomes, and iteratively improve code reliability. From NVIDIA Berkeley AI Research CMU Robotics Institute Stanford AI Lab 🧵
Max Fu169,218 просмотров • 2 месяцев назад
Tired of teleoperating your robots? We built a way to scale robot datasets without teleop, dynamic simulation, or even robot hardware. Just one smartphone scan + one human hand demo video → thousands of diverse robot trajectories. Trainable by diffusion policy and VLA models as-is. Introducing: Real2Render2Real 👉
Max Fu69,224 просмотров • 1 год назад
![Vision-language models perform diverse tasks via in-context learning. Time for robots to do the same! Introducing In-Context Robot Transformer (ICRT): a robot policy that learns new tasks by prompting with robot trajectories, without any fine-tuning. [1/N]](https://image.24vids.com/tw-1829235845985120618/ext_tw_video_thumb/1829235028871598081/pu/img/cVtUH50d7Q4sFesK.jpg)
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