Confidence-Based Supervised Autonomous Control for Robotic Suturing
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Solution Overview
Problem
Current robot-assisted surgery systems face challenges in achieving full autonomy in complex surgical environments, requiring human supervision for safety and accuracy, especially in deformable and unstructured soft tissue surgeries like knot tying and needle insertion.
Innovation Solution
A confidence-based supervised-autonomous control strategy that uses a suture planner algorithm to determine autonomous and human-intervention-required sutures, employing 3D sensing and graphical user interfaces for semi-autonomous suture placement adjustments, and a task planner to sequence robot motions for accurate suturing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If full autonomy is implemented in complex surgical environments, then productivity and consistency are improved, but reliability deteriorates due to lack of human supervision for safety
Solution Approach 1:
The surgical task is segmented into autonomous execution by the robot and supervisory control by the human surgeon. The system autonomously performs routine suturing tasks while the surgeon maintains oversight and intervention capability when needed, resolving the contradiction between productivity and reliability.
Solution Approach 2:
The system implements real-time feedback mechanisms where the surgeon can monitor autonomous suture placement and provide corrective input through the graphical user interface. This feedback loop ensures safety while maintaining high productivity through automated routine operations.
2Manufacturing precision
If autonomous control algorithms are used, then manufacturing precision and repeatability are improved, but device complexity increases due to need for human supervision interfaces
Solution Approach 1:
A graphical user interface serves as an intermediary between the complex autonomous control system and the human surgeon. This interface simplifies the interaction by providing intuitive controls for supervising autonomous suturing, thereby maintaining high precision without proportionally increasing user-side complexity.
Solution Approach 2:
The autonomous control system performs self-monitoring and self-adjustment based on confidence metrics, reducing the need for complex external supervision. The system automatically determines when human intervention is needed, simplifying the overall control architecture.
3Productivity
If pre-planned autonomous procedures are implemented, then productivity is improved, but adaptability deteriorates for deformable and unstructured soft tissue surgeries
Solution Approach 1:
The system transitions from static pre-planned procedures to dynamic adaptive control. The autonomous algorithm continuously adjusts its behavior based on real-time tissue deformation and surgical conditions, enabling it to handle deformable soft tissues while maintaining high productivity through automated execution.
Solution Approach 2:
The control system dynamically changes operational parameters based on tissue response and surgical progress. This allows the same autonomous framework to adapt to varying soft tissue conditions, maintaining both efficiency and versatility in procedures like knot tying and needle insertion.
Data Source
AI summary
A computer system, a computer-readable medium, and a computer-implemented method for robot-assisted suturing is disclosed. The computer-implemented method includes determining, by a suture planner algorithm executed by a hardware processor, a desired location for a suture for a potential suture location on a treatment area on a patient and determining which sutures from the suture planner algorithm can be done autonomously and which sutures may require human intervention to be performed.