Surgical Robot Pose Optimization for Optical Tracking Accuracy
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Solution Overview
Problem
Current surgical navigation systems face challenges in accurately positioning surgical tools due to manual adjustment limitations and potential interference with optical tracking systems, leading to reduced positioning accuracy and accessibility issues during robot-assisted surgeries.
Innovation Solution
An active navigation system that employs multi-objective optimization algorithms to determine optimal viewing angles and robot poses, combined with environmental perception sensors to ensure real-time adjustment and prevent interference, while planning and executing paths to achieve precise positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adjustment of optical navigation device is used, then ease of operation is improved, but positioning accuracy deteriorates
Solution Approach 1:
The patent transitions from static manual adjustment to dynamic automated adjustment. The robot system dynamically adjusts the optical navigation device's pose based on real-time surgical scene requirements, enabling adaptive positioning that maintains high accuracy while reducing manual intervention. The system automatically recalculates and repositions the navigation device during surgery to optimize measurement accuracy.
2Measurement precision
If robot actively adjusts optical navigation device, then positioning accuracy is improved, but device complexity increases
Solution Approach 1:
The patent merges the robot system with the optical navigation device by integrating sensors, controllers, and positioning tools into a unified system. This combination allows the robot to actively adjust the navigation device while sharing computational resources and control architecture, thereby improving positioning accuracy without proportionally increasing overall system complexity.
Solution Approach 2:
The robot system is designed with multi-functionality, serving both as a positioning platform and an adjustment mechanism for the optical navigation device. By making the robot universal in its capabilities, the system avoids adding separate dedicated adjustment hardware, thus improving positioning accuracy while controlling device complexity.
3Measurement precision
If special robot pose optimization is implemented, then positioning accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The system implements self-service through automated pose optimization algorithms that independently calculate and execute the optimal robot positions for navigation. The robot autonomously determines its own positioning requirements based on surgical scene data, eliminating the need for manual pose calculation and adjustment by surgeons, thereby improving accuracy while maintaining ease of operation.
Solution Approach 2:
The system employs feedback mechanisms where the robot continuously monitors the surgical scene and adjusts its pose based on real-time positioning requirements. The optimization algorithm receives feedback from sensor data and automatically refines the robot's position to maintain optimal measurement accuracy without requiring manual intervention.
4Reliability
If environmental perception sensors are added, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent combines environmental perception sensors with the existing optical navigation system, integrating multiple sensing functions into a unified architecture. By merging these sensor systems, the patent improves navigation reliability through enhanced environmental awareness while avoiding the complexity increase that would result from separate independent sensor systems.
Data Source
AI summary
An active navigation system of a surgery and a control method include: Step 1, measurement viewing angle multi-objective optimization: inputting position parameters of the positioning tools and setting other related parameters, and solving a set of optimal measurement viewing angles through multi-objective optimization; Step 2, a multi-objective decision of a pose of the robot: according to the set of optimal measurement viewing angles, recommending, to a user, an optimal pose scheme of the robot in each link of the surgery by using a multi-objective decision algorithm; or selecting the optimal pose scheme of the robot in each link of the surgery; and Step 3, planning and execution of a path of the robot: according to the selected optimal pose scheme of the robot in each link of the surgery, planning the path of the robot from the current pose to the optimal pose scheme.