Trocar And Robot Base Placement for Collision-Free Surgery
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Solution Overview
Problem
The manual placement of surgical robots in operating rooms can lead to suboptimal performance due to inappropriate positioning, necessitating adjustments during surgeries, which is inefficient and potentially risky.
Innovation Solution
A method and system for automated optimization of surgical instrument insertion location and robot base location using a simultaneous or sequential optimization framework, incorporating evaluation vectors and machine learning to identify optimal combinations based on spatial relationships and characteristics, ensuring efficient and risk-free robot-assisted surgeries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual placement of surgical robots is used, then ease of operation is improved, but placement precision and reliability deteriorate
Solution Approach 1:
The system enables automatic self-optimization of robot base and trocar locations through computational algorithms that analyze surgical goals, patient anatomy, and spatial constraints to determine optimal positions without human intervention, transforming a manual process into an autonomous one
Solution Approach 2:
The patent replaces manual mechanical positioning with an automated computational system that uses processing units to calculate optimal locations based on input data from surgical plans and patient models, substituting human expertise with algorithmic decision-making
2Device complexity
If manual robot placement is used, then device complexity is reduced, but reliability and surgical performance deteriorate
Solution Approach 1:
The system performs preliminary optimization calculations before surgery begins, determining the optimal robot base and trocar locations in advance based on preoperative imaging and surgical plans, so that when surgery starts, the positions are already predetermined and verified
Solution Approach 2:
The system incorporates feedback loops that evaluate the proposed locations against surgical goals and anatomical constraints, iteratively adjusting the optimization to ensure the selected positions meet all requirements for successful surgical execution
3Manufacturing precision
If automated optimization is implemented, then placement precision and reliability are improved, but device complexity and computational requirements worsen
Solution Approach 1:
The optimization system is segmented into distinct functional modules: input data processing, constraint analysis, optimization calculation, and location verification, allowing complex computations to be broken down into manageable steps that can be executed sequentially or in parallel
Data Source
AI summary
The present teaching relates to automated trocar/robot base location determination. An input relates to a surgical operation with a 3D model for an organ including cut points thereon forming a surgical trajectory. A surgical instrument is controlled by a robot to reach the cut points to carry out the surgical operation. Candidate combinations of insertion location for inserting the surgical instrument and base location for deploying the robot are generated. One of the candidate combinations is identified based on evaluation vectors associated therewith. Each evaluation vector provides assessment information on characteristics and spatial relationships of the respective candidate locations. The selected combination of locations is used for the surgical operation.