SOURCE-LINKED INTELLIGENCE

BiRoAD: Learning Shared and Role-Adaptive Representations for Bimanual Manipulation

arXiv · AI, language, vision and robotics · article · Sep 20, 2026 · UTC

Bimanual manipulation requires policies that coordinate two arms while adapting their functional roles to scene geometry, object configuration, and task context. Learning such scene-conditioned role adaptation remains challenging, as demonstrations may contain uneven role distributions that limit generalization to underrepresented arm--role configurations. In addition, many bimanual policies predict actions in fixed left- and right-arm action spaces. While this provides a natural parameterization for robot control, it does not explicitly specify how behaviors should transform when functional r

Read original source ↗ Open in workspace

recordType

paper

region

Global