Vision-Based Force Estimation for Telesurgical Instruments
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Solution Overview
Problem
Existing approaches for providing haptic feedback in telesurgery and other remote control applications are complex and limited in adapting to various environments, making it difficult to accurately estimate forces during instrument interactions with environmental structures.
Innovation Solution
A system and method for estimating forces between an instrument and an environmental structure using image data, where a processor estimates the spatial position of the instrument and, upon detecting contact, calculates the force based on the spatial position and classified contact condition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing approaches are used to provide haptic feedback, then feedback can be provided, but the system becomes complicated and limited in adapting to various environments
Solution Approach 1:
The patent replaces complex mechanical sensor systems with a vision-based system that uses image data and machine learning models to estimate force. Instead of relying on physical force sensors or complex haptic mechanisms, the system substitutes these with computational models that process visual information to infer contact conditions and force measures, thereby reducing hardware complexity while maintaining adaptability across different environments
Solution Approach 2:
The vision-based force estimation system provides universal applicability across multiple surgical instruments and environmental structures. The same image processing pipeline and machine learning models can estimate forces for different instrument-type environmental structure interactions, making the system versatile without requiring environment-specific sensors or calibration for each surgical scenario
2Measurement precision
If existing approaches are used to provide haptic feedback, then feedback can be provided, but the accuracy of force estimation is limited
Solution Approach 1:
The system replaces traditional force sensors with a vision-based estimation approach that uses image data processed through machine learning models. This substitution enables more accurate force estimation by leveraging visual information about contact conditions, instrument position, and environmental structure interactions, achieving superior measurement precision without the complexity of multiple sensor fusion systems
Solution Approach 2:
The patent creates a computational copy or model of the physical interaction between instruments and environmental structures. By training machine learning models on simulated or recorded interaction data, the system creates a virtual representation that can infer force characteristics from visual observations, achieving accurate force estimation through this digital twin approach rather than direct physical measurement
3Measurement precision
If external sensor measurements are used, then force can be measured directly, but the system requires additional sensors and becomes more complex
Solution Approach 1:
The patent extracts the force measurement function from separate external sensors and integrates it into the existing vision system. By processing image data that is already being captured for surgical visualization, the system extracts force information from the visual channel alone, eliminating the need for additional force sensors while maintaining measurement capability
Solution Approach 2:
The vision system is enhanced to serve multiple functions: it provides both the standard visual feedback for surgical procedures and simultaneously estimates force parameters. This multi-functionality allows the same imaging infrastructure to deliver both visualization and force measurement capabilities, avoiding the need for separate sensor systems
Data Source
AI summary
An example method includes estimating, by a processor, a spatial position of a portion of an instrument that is adapted to interact with an environmental structure to provide an estimated spatial position for the instrument, in which the spatial position is estimated based on image data that includes at least one image frame of the portion of the instrument and the environmental structure. The method also includes responsive to detecting contact between the instrument and the environmental structure, estimating, by the processor, a measure of force between the instrument and the environmental structure based on the estimated spatial position for the instrument.