Robot Path Segmentation for Linear-Circular Motion Accuracy
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Solution Overview
Problem
Existing methods for optimizing robot movement paths, particularly in industries like teeth mold cutting and precision machining, are inefficient and time-consuming, leading to wobbling and high communication loads due to the conflict between minimizing distance error and break points, with no effective optimization method to find the best combination of linear and circular movements.
Innovation Solution
A method utilizing genetic algorithms and dynamic programming to determine a target path by dividing the original path into sub-paths, selecting points for inclusion or exclusion, and optimizing these sub-paths as linear or circular based on error calculations, reducing the number of break points and improving path accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all points from the source point set are used in the robot path, then the path accuracy is improved, but the robot wobbling increases and communication load increases
Solution Approach 1:
The patent segments the dense point set into two categories: source points (which define the path geometry) and non-source points (which are used for error calculation but excluded from the final path). This segmentation allows the path to maintain high accuracy by including only necessary points while reducing robot wobbling by excluding redundant points from execution.
2Measurement precision
If all points from the source point set are used in the robot path, then the path accuracy is improved, but the communication load increases
Solution Approach 1:
The patent divides the point set into source points and non-source points, transmitting only source points to the robot while using non-source points for offline error calculation. This reduces communication load by filtering out redundant points while maintaining path accuracy through the error evaluation mechanism.
3Measurement precision
If the number of break points is increased to reduce distance error, then the path accuracy is improved, but the path complexity increases
Solution Approach 1:
The patent implements a feedback mechanism where the distance error between the original path and the optimized path is calculated and used to iteratively adjust the selection of source points and the determination of break points. This feedback loop continues until the error meets the required threshold, ensuring optimal path accuracy without excessive complexity.
Solution Approach 2:
The patent changes the parameter of break point placement from fixed intervals to dynamic placement based on error distribution. Break points are positioned at locations where the distance error exceeds a threshold, allowing the path to achieve required accuracy while minimizing the total number of break points and reducing path complexity.
4Measurement precision
If the best fitness is calculated by evaluating all solutions, then the path optimization is improved, but the calculation time increases
Solution Approach 1:
The patent segments the evaluation process into two stages: first, filter and select source points from the dense point set to reduce the search space; second, perform break point optimization only on the reduced set of source points. This segmentation dramatically reduces calculation time while maintaining optimization quality by avoiding exhaustive evaluation of all possible paths.
Solution Approach 2:
The patent applies partial action by evaluating only the most promising paths rather than all possible solutions. The error threshold mechanism allows the algorithm to stop when sufficient optimization is achieved, avoiding unnecessary calculations and reducing time loss while still obtaining high-quality path optimization.
Data Source
AI summary
A method for obtaining a target path of a robot includes obtaining a plurality of points of an original path of the robot; determining, among the plurality of points, a first set of points to be included in the target path of the robot and a second set of points to be excluded from the target path; and determining the target path by determining, based on the first set of points and the second set of points, at least one sub-path of the target path as linear or circular.