Robot manipulation data collection has been shifting from teleoperation toward robot-free demonstrations, through interfaces such as the Universal Manipulation Interface (UMI) or directly from human hands. Vision-Language-Action (VLA) policies trained on such data inherit the demonstrator's timing. Yet human timing doe...
Mimo Shirasaka, Takehiko Ohkawa, Takuya Okubo et al.· 0 citations
Multimodal Probabilistic Fusion (MMPF), a training-free auditing framework that treats each modality as an expert, estimates a task-label distribution from local neighborhood agreement and global prototype similarity, and then fuses modalities with predictive-entropy weighting in a product of experts is proposed.
Simon Holk, Ryosuke Takanami, T. Matsushima et al.· IEEE Robotics and Automation...· 0 citations
This work synthesizes counterfactual instruction-observation-action tuples from the dataset and combines them with adversarial discriminator training to learn an instruction-grounded reward model for offline RL, without collecting additional rollouts or annotations.
Haruo Kondoh, Keita Ota, Asako Kanezaki et al.· 1 citation
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