BiPreManip: 通过预见性协作学习基于 affordance 的双臂预备操作
BiPreManip: Learning Affordance-Based Bimanual Preparatory Manipulation through Anticipatory Collaboration
AI总结：
本文提出BiPreManip框架，通过预见性协作学习双臂预备操作，提升任务成功率和泛化能力。
摘要：
许多日常物品难以直接抓取（例如平放的iPad）或功能操作（例如打开桌上的笔帽）。此类任务需要双臂的顺序、非对称协调，其中一只手臂进行预备操作以使另一只手臂的目标动作得以实现——例如在拿起iPad前将其推到桌子边缘，或提起笔身以让另一只手去除其帽。本文引入了协作预备操作，一种需要理解物体语义和几何、预测空间关系以及规划长时段双臂协调动作的双臂操作任务。为解决这一挑战，我们提出了一种基于视觉affordance的框架，首先设想最终的目标动作，然后引导一只手臂执行一系列预备操作以促进另一只手臂的后续操作。这种以affordance为中心的表示方法能够实现预见性双臂推理和协调，在各种不同类别物体上表现出良好的泛化能力。在仿真和现实世界中的大量实验表明，与竞争基线相比，我们的方法显著提高了任务成功率和泛化能力。
英文摘要：
Many everyday objects are difficult to directly grasp (e.g., a flat iPad) or manipulate functionally (e.g., opening the cap of a pen lying on a desk). Such tasks require sequential, asymmetric coordination between two arms, where one arm performs preparatory manipulation that enables the other's goal-directed action - for instance, pushing the iPad to the table's edge before picking it up, or lifting the pen body to allow the other hand to remove its cap. In this work, we introduce Collaborative Preparatory Manipulation, a class of bimanual manipulation tasks that demand understanding object semantics and geometry, anticipating spatial relationships, and planning long-horizon coordinated actions between the two arms. To tackle this challenge, we propose a visual affordance-based framework that first envisions the final goal-directed action and then guides one arm to perform a sequence of preparatory manipulations that facilitate the other arm's subsequent operation. This affordance-centric representation enables anticipatory inter-arm reasoning and coordination, generalizing effectively across various objects spanning diverse categories. Extensive experiments in both simulation and the real world demonstrate that our approach substantially improves task success rates and generalization compared to competitive baselines.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
