PA-BiCoop: A Primary-Auxiliary Cooperative Framework for General Bimanual Manipulation
2026-06-26 • Robotics
Robotics
AI summaryⓘ
The authors created a new way for robots with two arms to work together better by letting one arm do the main job while the other helps out, changing their roles as needed during a task. Their system, called PA-BiCoop, uses special parts that plan movements for each arm, sharing information between them to improve coordination. Tests showed that their method works much better than older ones, both in simulations and with real robots. So, their approach helps two-armed robots handle tasks more efficiently and flexibly.
Bimanual manipulationRobotic armsDynamic role assignmentPose estimationTask affordanceCoordinationReinforcement LearningSimulation tasksReal-world roboticsMulti-arm cooperation
Authors
Bai Qicheng, Wang Ziru, Ma Teli, Dai Guang, Wang Jingdong, Wang Mengmeng
Abstract
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.