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simmediummobile-manipulationmetric · varies
AIRoA MoMa Dataset: A Large-Scale Hierarchical Dataset for Mobile Manipulation
Description
As robots transition from controlled settings to unstructured human environments, building generalist agents that can reliably follow natural language instructions remains a central challenge. Progress in robust mobile manipulation requires large-scale multimodal datasets that capture contact-rich and long-horizon tasks, yet existing resources lack synchronized force-torque sensing, hierarchical annotations, and explicit failure cases. We address this gap with the AIRoA MoMa Dataset, a large-sca