团队开源智能体机器人框架CaP-X,包含感知、控制、可视化工具,并发布CaP-Gym和CaP-Bench基准,CaP-RL使7B模型成功率从20%提升至72%,程序可迁移至真实机器人。
The power of the Claw, in the palm of a robot hand. Agentic robotics is here! Today, we open-source CaP-X: vibe agents, alive in the physical world. They incarnate as robot arms and humanoids with a rich set of perception APIs, actuation APIs, and auto synthesize skill libraries as they go. CaP-X is a strict superset of our old stack, because policies like VLAs are “just” API calls as well. It solves many tasks zero-shot that a learned policy would struggle with.
And we are doing much more than vibing. CaP-X is our most systematic, scientific study on agentic robotics so far:
3 years ago, our team created Voyager, one of the earliest agentic AI that plays and learns in Minecraft continuously. Its key ideas — skill libraries, self-reflection loops, and in-context planning — have since influenced many modern agentic designs.
Today, the agent graduates from Minecraft and gets a real job. It’s April Fool’s, but this Claw is getting its hands dirty for real!
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