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Rohan Paul· @rohanpaul_ai · X· · 原发布时间 AI 评分54

斯坦福论文提出让编码模型自动改写机器人控制代码

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RoboArchitect 让编码模型查看机器人尝试的录像、诊断失败,并在最多 5 轮中改写控制代码,无需更新模型权重。模拟测试中,面对未见过的场景,平均成功率从原策略的 9.7% 升至 43.3%;面对未见过的任务,则从 12.7% 升至 40.2%。

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New Stanford paper shows that robot control code no longer needs hand-building for each new robot, because a coding model can diagnose failures and rewrite it automatically.

Robot policies often fail on new setups, and fixing them usually means new demonstrations and finetuning. Wrapping the policy in control code helps, but engineers write it by hand for each robot.

RoboArchitect has a coding model review recorded robot attempts, diagnose failures, and rewrite the control code over up to 5 rounds. A full run cost under $150 on average, with no weights updated.

On unseen scenes, average success rose from 9.7% for the bare policy to 43.3%, and on unseen tasks from 12.7% to 40.2%. On VLABench, the wrapped general policy beat the same policy finetuned on that benchmark, though all tests ran in simulation.

来源:Rohan Paul · x.com

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