Real-Time Tracking of Flexible Surfaces Using Dynamic Deformation Models
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Solution Overview
Problem
Current methods for real-time tracking of moving flexible surfaces in surgical robotics fail due to the need for accurate physical modeling, which is not validated with real tissues, and are ineffective during occlusions or when surfaces fold, limiting their applicability in deformable tissue manipulation.
Innovation Solution
A method involving a vision system that acquires and processes stereo camera images to compute 3D point cloud data, fits parametric surfaces, and applies both rigid and stretching transformations to track moving flexible surfaces, enabling real-time tracking of deformable tissues by synchronously acquiring and processing image frames to calculate the location of regions of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical models with optimized parameters are used for tracking, then tracking accuracy can be improved under ideal conditions, but the system fails when surfaces fold or are occluded
Solution Approach 1:
The system dynamically adapts the deformation model based on observed surface behavior. Instead of using a fixed physical model, the algorithm adjusts the deformation characteristics in real-time to match the actual tissue behavior, allowing it to handle various deformation types including folding and occlusion without requiring precise pre-modeling of all possible scenarios
Solution Approach 2:
The system changes the parameters of the deformation model based on observed data. By continuously updating the model parameters from visual observations rather than relying on pre-identified physical parameters, the system can adapt to different tissue types and deformation modes, improving both accuracy and robustness across varying conditions
2Adaptability or versatility
If complex physical models are used to account for all deformation types, then tracking coverage can be improved, but computational complexity and model validation requirements increase
Solution Approach 1:
The system segments the deformation analysis into local regions rather than modeling the entire surface with a single complex physical model. By dividing the surface into smaller patches and applying simpler deformation models to each local region, the system achieves comprehensive coverage of various deformation types while keeping individual model complexity low
Solution Approach 2:
The system replaces complex mechanical physical modeling with visual observation-based modeling. Instead of using physics-based equations that require validation with real tissues, the system derives deformation characteristics directly from image sequences, substituting mechanical models with computer vision-based approaches that are more adaptable and easier to implement
3Productivity
If real-time processing is implemented, then surgical application feasibility is improved, but processing speed requirements increase computational demands
Solution Approach 1:
The system uses dynamic model adaptation that processes only the necessary changes between frames rather than re-processing the entire surface. By tracking the evolution of deformation parameters over time and updating only the changed regions, the system achieves real-time performance with reduced computational power requirements
Solution Approach 2:
The system applies partial processing by focusing computational resources on regions of interest or areas with significant deformation rather than processing the entire surface uniformly. This selective approach maintains real-time capability while reducing overall computational demands
Data Source
AI summary
The present invention provides a method for real-time tracking of moving flexible surfaces and an image guided surgical robotic system using this tracking method. A vision system acquires an image of the moving flexible surface and identifies and tracks visual features at different times. The method involves computing both rigid and stretching transformations based on the changing positions of the visual features which are then used to track any area of interest on the moving flexible surface as it evolves over time. A robotic surgical system using this real-time tracking is disclosed.