Robotic Therapy Control Using Fused Sensing for Soft Tissue Deformation
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Solution Overview
Problem
Current robotic systems are not equipped to handle soft body tissues effectively due to their non-uniform consistency and unique characteristics, which existing device testing and medical procedures systems are not configured to manage in an automated and dynamic manner.
Innovation Solution
A robotic control system utilizing a fused sensing stream and Finite Element Analysis model to predict tissue deformation, adjust parameters, and maintain precise alignment and force to treat soft tissues, allowing for automated and dynamic handling of soft body tissues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time controlled robotic systems are used for medical procedures, then precise control and monitoring of robotic actions is improved, but the ability to handle soft body objects with non-uniform consistency deteriorates
Solution Approach 1:
The robotic system transitions from static, pre-programmed control to dynamic, real-time adaptation through continuous sensing and control loop adjustments. The system dynamically modifies its control parameters based on real-time tissue response feedback, enabling it to handle non-uniform soft body objects effectively while maintaining precise control.
Solution Approach 2:
The system implements a closed-loop control architecture with continuous feedback from multiple sensors (force, torque, position) that monitor tissue interaction in real-time. This feedback enables the robotic system to detect tissue inconsistencies and automatically adjust its control parameters, resolving the contradiction between control precision and adaptability to varying tissue properties.
2Productivity
If automated robotic systems are implemented for device testing, then productivity and consistency are improved, but the ability to manage unique characteristics of each soft body sample deteriorates
Solution Approach 1:
The robotic system performs self-adjustment through autonomous decision-making based on real-time sensor data. When encountering unique characteristics of a soft body sample, the system automatically modifies its testing protocol and control parameters without human intervention, maintaining both high productivity and sample-specific adaptability.
Solution Approach 2:
The testing system dynamically adapts its操作流程 based on real-time characterization of each sample's unique properties. The system transitions from rigid, standardized testing to flexible, sample-specific protocols while maintaining automated operation, thus preserving productivity gains while achieving sample-specific handling capability.
3Force
If robotic end effectors apply force to soft tissue, then treatment effectiveness is improved, but tissue deformation and mechanical property changes worsen control predictability
Solution Approach 1:
The system employs predictive modeling and simulation to anticipate tissue deformation and mechanical property changes before applying treatment force. By pre-calculating the effects of intended forces and preparing compensatory control adjustments, the system maintains control reliability even as tissue properties change during treatment.
Solution Approach 2:
The robotic system uses real-time feedback from force sensors and position sensors to continuously monitor actual tissue response during treatment. This feedback enables dynamic compensation for unexpected deformations and mechanical property changes, maintaining control reliability while applying effective treatment forces.
Data Source
AI summary
A system, method, and apparatus are provided for a robotic system effecting autonomous therapy or treatment of a body having soft and/or hard tissue. A system, method, and apparatus are provided for a robotic control system having a fused sensing stream for predicting the deformation of a robotic end effector and the tissue that the end effector is in contact with using, e.g., a Finite Element Analysis (FEA) model. The model updates provide adjustment parameters for the control system to compensate for changes in the mechanical nature of the robotic end effector and the characteristics and/or movement of the tissue being treated by the robotic end effector.