Flexible Needle Path Planning Using Artificial Potential Field
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Solution Overview
Problem
Traditional path planning methods for flexible needle puncture surgery in soft tissue environments are limited by their failure to consider kinematic characteristics and real-time operation requirements, leading to low accuracy and increased risk of tissue damage due to instability and deviation from optimal solutions.
Innovation Solution
An artificial potential field path planning method is introduced, which classifies obstacles and uses a potential energy function based on soft tissue characteristics to optimize the path planning of flexible needles, incorporating curvature constraints and optimization indices to improve trackability and reduce uncertainty in needle motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional path planning methods are used for flexible needle puncture, then a geometric path can be realized, but the method does not consider kinematic characteristics of the flexible needle, leading to low puncture accuracy and instability
Solution Approach 1:
The patent transforms the path planning problem from a geometric approach to a potential field approach by changing the fundamental parameters of the method. It introduces potential energy functions with attraction and repulsion components, and incorporates kinematic constraints as additional parameters in the optimization process, thereby achieving both accuracy and stability
Solution Approach 2:
The patent replaces the traditional geometric path planning mechanism with an artificial potential field mechanism. Instead of calculating geometric paths directly, the system uses potential energy fields to guide the needle, substituting a mechanical geometric calculation system with a physics-based field system that naturally handles kinematic constraints
2Reliability
If traditional barriers model is used for obstacle avoidance, then obstacle protection is achieved, but the model may lead to loss of optimal solution and no solution for puncture treatment
Solution Approach 1:
The patent applies local quality by differentiating obstacle characteristics through classification. Different tissue types (vital organs, nerves, blood vessels, etc.) are assigned different repulsion coefficients based on their importance and vulnerability. This allows the system to protect critical structures while maintaining flexibility to pass through or around less critical tissues, preserving optimal paths
Solution Approach 2:
The patent introduces dynamic adaptation in the potential field model. The repulsion field strength is not fixed but varies based on obstacle classification and real-time needle position. This dynamic adjustment allows the system to adapt to different surgical scenarios, maintaining both safety and optimality where traditional static barrier models fail
3Device complexity
If unified optimization index is used for path planning, then optimization is simplified, but it is insufficient to shed light on the specific influence on actual path by the various components of the optimization index
Solution Approach 1:
The patent segments the unified optimization index into distinct components: attraction potential energy, repulsion potential energy, and kinematic constraint terms. Each component has a specific physical meaning and can be independently analyzed and adjusted. This segmentation allows the system to maintain simplicity while achieving precise control over path characteristics
Solution Approach 2:
The patent incorporates curvature constraints in the optimization index to account for the flexible needle's kinematic characteristics. The curvature term ensures that the planned path is physically realizable for a flexible needle, providing specific guidance on how path geometry affects actual needle behavior rather than just providing a unified abstract optimization criterion
4Speed
If rapid expanding random search tree method is used for path planning, then path finding speed is improved, but the method has solving instability and deviation from optimal solution
Solution Approach 1:
The artificial potential field method is inherently self-guiding and does not require external iterative search algorithms. The gradient of the potential field automatically guides the needle from start to goal while avoiding obstacles, eliminating the need for random search trees or other iterative optimization methods, thus achieving both speed and accuracy
Data Source
AI summary
An artificial potential field path planning method and an apparatus based on obstacle classification solve the problem of path and motion uncertainty in steering a flexible needle in soft tissue. The apparatus includes an image sensing system, a control module, an execution system and an upper PC. Using the apparatus, the method includes: the image sensing system obtains real-time images of the puncture environment, identifies a target and obstacles from the real-time images, classifies the obstacles, and calculates total potential energy of points in the current environment based on artificial potential field. With a curvature constraint and an optimization index for the flexible needle, the path planning module carries out static path planning to obtain an initial path and the needle entry point, then conducts dynamic path planning to determine the path for steering the flexible needle in the soft tissue accordingly.