arXiv:2610.41946v1 Announce Type: new
Abstract: Embodied surgical AI requires reliable multimodal data, yet surgical data collection remains costly, difficult to repeat, and strongly dependent on the hardware setup. We present Sensorium, an open-source Python library for recording, processing, annotating, and curating multimodal surgical data from configurable robot and sensor streams using the Robot Operating System (ROS) and ROS2 middleware. The library combines operator-facing data acquisition, configurable processing, semantic annotation, and episodic dataset generation. We evaluate Sensorium across 1516 recordings of phantom, ex vivo, and in vivo porcine experiments involving multiple surgical tasks and sensing configurations, and report preliminary usability feedback.
arxiv
Sensorium: Open-Source Library for Multimodal Surgical Data Collection
Sensorium is an open-source Python library for recording, processing, annotating, and curating multimodal surgical data from robot and sensor streams using ROS/ROS2. It was evaluated across 1516 recordings from phantom, ex vivo, and in vivo porcine experiments. The library aims to reduce cost and improve repeatability in embodied surgical AI data collection.
Provides a concrete open-source tool addressing a key bottleneck in surgical AI, with substantial evaluation data.
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