Multimodal Metrics and Event Detection for Robotic Bronchoscopy

The patent merges robot data, image data, and sensor data into a unified contextual information generation system. The control circuitry integrates multiple data modalities by accessing repositories storing these diverse data types and processing them together to generate comprehensive contextual information, thereby improving control and safety while managing system complexity through structured integration.

The control circuitry serves multiple functions: it generates change data from image data, accesses robot logs, processes sensor data, and generates contextual information. This multi-functional approach consolidates various processing tasks into a single system component, improving reliability while avoiding proportional increases in overall system complexity.

The patent segments the data processing task into distinct functional components: an image processing portion that generates change data from image data, a robot data portion that accesses and processes robotic commands and states, and a sensor data portion that processes sensor readings. This segmentation allows each component to specialize in processing specific data modalities, improving measurement precision while managing complexity through modular organization.

The control circuitry acts as an intermediary that receives and processes multiple data modalities from different sources (image data from imaging devices, robot data from robotic systems, sensor data from sensors). It mediates between these diverse data types by generating unified contextual information that integrates all modalities, thereby improving measurement precision without requiring direct complex interactions between all data sources.