RAPID:从单次人类演示自动生成并验证机器人程序
RAPID: Robot Agentic Programming from Demonstrations
论文教会编程智能体看一遍人类演示就能自己写机器人代码,还能在真 Franka 机械臂上跑通 8 个操作任务,做机器人方向的朋友可以看看。
RAPID 是一个把编程智能体引入机器人系统的框架,只需一段视觉人类演示即可自动生成、验证并迭代修正机器人程序。它能从演示中自动推断三要素:可测试的任务规范、动作原语和用于程序验证的交互环境。程序采用以物体为中心的关系式表示,用轨迹优化程序实现物体级运动效果,并通过关系约束在运行时捕捉场景几何。在 8 个接触丰富的非抓取操作任务和 LIBERO-Pro 基准上完成仿真评估,并在真实 Franka 机械臂上部署验证,对物体位姿、形状、材质和环境变化具备泛化能力。
RAPID: Robot Agentic Programming from Demonstrations
Coding agents have demonstrated enormous success in solving complex programming problems. To leverage their potential for robot systems, this work introduces Robot Agentic Programming from Demonstrations (RAPID), which automatically generates, verifies, and refines robot programs, given a single visual human demonstration. The iterative agentic loop of code refinement requires several key ingredients: (i) a testable task specification, (ii) action primitives for robot execution, and (iii) an interactive environment for program execution and verification. RAPID infers all three from the demonstration automatically. To make the resulting program reusable beyond the demonstration setting, RAPID uses an object-centric relational program representation that focuses on the underlying structure of the demonstrated strategy rather than the specific motion per se: it expresses the action primitives as trajectory-optimization programs that realize object-level motion effects, while composing them through relational constraints that capture scene-specific geometry at run time. We evaluated RAPID in simulation on eight challenging contact-rich nonprehensile manipulation tasks as well as general prehensile manipulation tasks in the LIBERO-Pro benchmark. We also successfully deployed it on a real Franka arm and evaluated on all eight nonprehensile tasks. In all experiments, RAPID demonstrated strong performance, with generalization over object pose, shape, material, and environment. Website: https://yuyaoliu.me/projects/rapid.