斯坦福大学研究团队推出了 RoboArchitect,利用编码模型审查机器人操作失败并自动重写控制代码。在不更新模型权重的情况下,该方法在未见过场景和任务上的平均成功率显著提升,且成本较低。
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