用图模型预测积木移除后果，让机械臂安全玩难版杰尼卡游戏。
Strategic Jenga Play via Graph Based Dynamics Modeling
- 构建积木结构图，判断某块移除是否导致倒塌。
- 训练动态模型预测每步积木运动，实现安全抽块。
- 适合研究机器人接触操控与复杂系统推理的学者。
在接触丰富的操作任务中，控制多个相互关联物体的动态是一个挑战，需要理解一个物体的运动如何影响其他物体。以杰尼卡游戏为测试平台，我们采用基于图的建模方法解决两个关键问题：1）积木选择；2）积木提取。针对积木选择，我们构建杰尼卡塔的图结构，基于其拓扑判断移除某块是否会引发倒塌。针对积木提取，我们训练一个动态模型，预测每次提取轨迹中所有积木在每个时间步的运动状态，并将其集成到基于采样的模型预测控制循环中，从而使用通用平行夹爪安全地抽出积木。我们在模拟环境中训练和评估该方法，在一系列全尺寸杰尼卡塔上展示了对积木选择与提取的出色表现，即使在游戏后期阶段也具备可行性。
原文摘要 · Abstract (English)
Controlled manipulation of multiple objects whose dynamics are closely linked is a challenging problem within contact-rich manipulation, requiring an understanding of how the movement of one will impact the others. Using the Jenga game as a testbed to explore this problem, we graph-based modeling to tackle two different aspects of the task: 1) block selection and 2) block extraction. For block selection, we construct graphs of the Jenga tower and attempt to classify, based on the tower's structure, whether removing a given block will cause the tower to collapse. For block extraction, we train a dynamics model that predicts how all the blocks in the tower will move at each timestep in an extraction trajectory, which we then use in a sampling-based model predictive control loop to safely pull blocks out of the tower with a general-purpose parallel-jaw gripper. We train and evaluate our methods in simulation, demonstrating promising results towards block selection and block extraction on a challenging set of full-sized Jenga towers, even at advanced stages of the game.
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