PA-BiCoop: 一种通用双臂操作的主辅协作框架
PA-BiCoop: A Primary-Auxiliary Cooperative Framework for General Bimanual Manipulation
AI总结：
提出PA-BiCoop框架，通过动态主辅臂角色分配和共享编码器-双解码器结构，实现双臂协调操作，在仿真和真实任务中平均性能提升超48%。
摘要：
双臂操作对于先进机器人系统至关重要，因为与单臂配置相比，它提供了更高的效率和灵活性。然而，现有方法要么缺乏臂间交互，要么忽略了动态分工的需求，将双臂视为功能等效。为了解决这些限制，本文从人类双臂操作中汲取灵感，其中一只手臂处理核心操作，另一只提供辅助支持，并提出了PA-BiCoop，一种新的具有动态主辅臂区分的单模型双臂协作框架。PA-BiCoop将机械臂分为主臂和辅臂，其角色在任务阶段中自适应调整，采用两个共享全局特征编码器的专用解码器：主解码器生成主臂的基坐标姿态和核心任务可操作度热图，辅解码器输出辅臂在主臂坐标系中的相对姿态。此外，我们设计了一个动态角色分配模块，自动将角色映射到左/右臂，无需手动预定义。这种设计促进了臂间知识共享和协调操作。大量实验表明，我们的PA-BiCoop实现了优越的性能：在RLBench2仿真任务中平均比最先进的基线高出48%，在真实世界任务中平均高出50%以上，从而验证了其在双臂操作中的有效性和先进性。
英文摘要：
Bimanual manipulation is essential for advanced robotic systems because it offers higher efficiency and flexibility compared to single-arm configurations. However, existing approaches either lack inter-arm interaction or ignore the need for a dynamic division of labor, treating the arms as functionally equivalent. To address these limitations, this paper draws inspiration from human bimanual manipulation where one arm handles core operations and the other provides auxiliary support, and proposes PA-BiCoop, a new single-model bimanual cooperation framework with dynamic primary-auxiliary arm differentiation. PA-BiCoop categorizes robotic arms into primary and auxiliary arms with adaptively adjustable roles across task stages, employs two specialized decoders that share a global feature encoder: the primary decoder generates the primary arm's base-coordinate pose and core-task affordance heatmaps, and the auxiliary decoder outputs the auxiliary arm's relative pose in the primary arm's coordinate system. Moreover, we design a dynamic role assignment module to automatically map roles to left/right arms without manual pre-definition. This design facilitates inter-arm knowledge sharing and coordinated manipulation. Extensive experiments demonstrate that our PA-BiCoop achieves superior performance: it outperforms state-of-the-art baselines by 48% on average in RLBench2 simulation tasks and by over 50% on average in real world tasks, thereby verifying its effectiveness and advancement in bimanual manipulation.
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。
