AnyBimanual: Transferring Unimanual Policy for General Bimanual Manipulation
Guanxing Lu, Tengbo Yu, Haoyuan Deng, Season Si Chen, Yansong Tang,, Ziwei Wang

TL;DR
AnyBimanual is a plug-and-play approach that transfers pre-trained unimanual policies to bimanual manipulation tasks, significantly reducing data requirements and improving success rates in both simulated and real-world environments.
Contribution
The paper introduces a novel method combining skill management and visual alignment to effectively transfer unimanual policies to bimanual tasks with minimal demonstrations.
Findings
Achieved 12.67% higher success rate on simulated tasks.
Demonstrated 84.62% average success rate on real-world tasks.
Outperformed previous methods in general bimanual manipulation.
Abstract
Performing general language-conditioned bimanual manipulation tasks is of great importance for many applications ranging from household service to industrial assembly. However, collecting bimanual manipulation data is expensive due to the high-dimensional action space, which poses challenges for conventional methods to handle general bimanual manipulation tasks. In contrast, unimanual policy has recently demonstrated impressive generalizability across a wide range of tasks because of scaled model parameters and training data, which can provide sharable manipulation knowledge for bimanual systems. To this end, we propose a plug-and-play method named AnyBimanual, which transfers pre-trained unimanual policy to general bimanual manipulation policy with few bimanual demonstrations. Specifically, we first introduce a skill manager to dynamically schedule the skill representations discovered…
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Taxonomy
TopicsSoftware Reliability and Analysis Research
Methodstravel james · ALIGN
