Article

Action-Conditioned World Model for Robotic Neck Ultrasound Target Plane Guidance

This study proposes a local action-conditioned world model framework for probe guidance toward target planes in robotic ultrasound, using a two-stage model-based learning pipeline: first, a latent conditional diffusion world model predicts future ultrasound observations from recent context frames, probe motion, and temporal offset; second, a goal-conditioned temporal Transformer predicts ordered probe actions and is fine-tuned using rewards from the frozen world model.

Part of the event: Proposal of a Framework for Target-Plane-Guided Robotic Neck Ultrasound

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