用扩散模型根据轮廓生成稳定积木结构，让机器人像人一样理解物理稳定性。
StackGen: Generating Stable Structures from Silhouettes via Diffusion
- 基于扩散模型，从目标轮廓生成多种稳定堆叠方案。
- 在仿真和真实机器人上验证，能成功搭建复杂稳定结构。
- 适合对物理推理与具身智能感兴趣的研究者。
人类通过观察和互动世界，自然获得对刚性物体之间相互作用及稳定性的直觉，从而用日常物品构建复杂结构。而传统机器人需依赖详细的物体几何和环境动力学模型，难以扩展且缺乏泛化能力。为此，我们提出 StackGen，一种基于扩散模型的方法，可根据目标轮廓生成多样化的稳定积木配置。通过在仿真环境中评估，并在真实场景中使用机械臂组装模型生成的结构，验证了该方法的有效性。结果表明，该方法能生成符合物理稳定性的多样化构型，为机器人提供类似人类的直观物理认知能力。
原文摘要 · Abstract (English)
Humans naturally obtain intuition about the interactions between and the stability of rigid objects by observing and interacting with the world. It is this intuition that governs the way in which we regularly configure objects in our environment, allowing us to build complex structures from simple, everyday objects. Robotic agents, on the other hand, traditionally require an explicit model of the world that includes the detailed geometry of each object and an analytical model of the environment dynamics, which are difficult to scale and preclude generalization. Instead, robots would benefit from an awareness of intuitive physics that enables them to similarly reason over the stable interaction of objects in their environment. Towards that goal, we propose StackGen, a diffusion model that generates diverse stable configurations of building blocks matching a target silhouette. To demonstrate the capability of the method, we evaluate it in a simulated environment and deploy it in the real setting using a robotic arm to assemble structures generated by the model.
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