Surgical Robotic Control Through Switching Models for Intraocular Safety
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Solution Overview
Problem
The potential for human operators to unintentionally inflict damage during intraocular procedures due to incorrect control of surgical instruments in surgical robotic systems, particularly when extensive control is required, is a challenge that existing model-assisted control methods struggle to address effectively.
Innovation Solution
A surgical robotic system that employs multiple models to model the surgical environment, adapt to sensor data, and switch between these models based on predefined criteria to enhance model-assisted control, thereby improving the precision and safety of instrument positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a human operator directly controls the surgical instrument's pose, then the operator can make real-time decisions, but the risk of unintentional damage increases due to incorrect control
Solution Approach 1:
The patent introduces a model-based virtual bound as an intermediary between the human operator and the surgical instrument. The model predicts the surgical target's position and creates a virtual boundary that automatically limits the instrument's movement range. This mediator prevents dangerous movements without requiring the operator to manually calculate safe zones, thus improving safety while maintaining operational simplicity.
Solution Approach 2:
The system continuously updates the model with sensor data during the procedure and dynamically adjusts the virtual bound accordingly. This real-time feedback loop ensures that the safety boundaries remain accurate even as the surgical target moves or deforms, allowing the operator to work within continuously updated safe zones without increased cognitive load.
2Measurement precision
If a single model is used for model-assisted control, then the system is simpler, but the model may become inaccurate when surgical conditions change
Solution Approach 1:
The patent divides the modeling task into multiple specialized models, each optimized for specific surgical conditions or anatomical regions. Instead of one general model that must handle all scenarios, the system uses segmented models that can be selected or combined based on the current surgical context, improving accuracy without requiring an overly complex single model.
Solution Approach 2:
The system dynamically selects or switches between different models based on real-time surgical conditions. When the surgical environment changes (e.g., tissue deformation, instrument position changes), the system adapts by activating the most appropriate model, maintaining accuracy throughout the procedure without the complexity of a static comprehensive model.
Data Source
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AI summary
A surgical robotic system and method for control of the surgical robotic system are provided. The surgical robotic system is configured to hold a surgical instrument 119 and to provide model-assisted control of the surgical instrument during an intraocular procedure. To establish the model-assisted control of the surgical instrument, the surgical robotic system and method may access model data defining at least two models which each model at least part of the surgical environment, evaluate one or more switching criteria that define conditions for switching between the first model 230 and the second model 240 for the model-assisted control, and when the switching criteria are met, switch between both models in the model-assisted control. By being able to switch between different models, it may not be needed for a single model to be universally applicable in all situations during the intraocular procedure, which may be exceedingly difficult and/or may greatly increase the complexity of a single model beyond the combined complexity of two or more separate models.