Robot Control Parameter Display for Motion Time and Accuracy Tradeoffs
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Solution Overview
Problem
Existing techniques for setting control parameters for robots often fail to simultaneously optimize multiple evaluation indexes such as motion time and trajectory accuracy, leading to unsatisfactory results where one index is prioritized over the others, requiring complex changes in optimization purposes and weight determination.
Innovation Solution
A method using a multi-objective optimization technique with a function containing motion time and trajectory accuracy as objective functions to determine new parameter sets, repeatedly evaluating and displaying parameter sets that satisfy both indexes, allowing users to select optimal parameters based on graphical representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a parameter is optimized for shortening motion time, then motion time is improved, but trajectory accuracy deteriorates
Solution Approach 1:
The patent applies parameter changes by transforming the multi-objective optimization problem into a single-objective optimization problem through weighted summation. Multiple evaluation indexes (motion time, trajectory accuracy, energy consumption) are converted into a composite objective function with adjustable weights, allowing the system to find optimal parameter sets that balance competing requirements without manual trial-and-error
2Manufacturing precision
If a parameter is optimized for trajectory accuracy, then trajectory accuracy is improved, but motion time deteriorates
Solution Approach 1:
The system transforms the optimization problem by creating a weighted sum objective function that incorporates both trajectory accuracy and motion time with adjustable weights. This allows the optimization algorithm to simultaneously consider both evaluation indexes and generate parameter sets that achieve satisfactory balance, eliminating the need to switch between single-objective optimizations
3Adaptability or versatility
If multiple single-objective optimizations are performed to satisfy multiple evaluation indexes, then comprehensive optimization is improved, but device complexity deteriorates
Solution Approach 1:
The patent merges multiple single-objective optimization problems into a single multi-objective optimization framework. By combining multiple evaluation indexes into one composite objective function with weighted summation, the system performs comprehensive optimization in a unified process rather than through multiple separate optimization procedures, thereby reducing complexity while maintaining adaptability
Solution Approach 2:
The system introduces weight parameters as additional design variables that control the relative importance of different evaluation indexes. By changing these weight parameters, the optimization can adapt to different user requirements and generate appropriate parameter sets without requiring multiple separate optimization procedures for different purposes
Data Source
AI summary
(a) Determine first, second indexes. (b) Acquire values of the first, second indexes after a robot works using a parameter set. (c) Determine a new parameter set using a multi-objective optimization technique with a function containing the first, second indexes as an objective function. (d) Acquire values of the first, second indexes using the new parameter set. (e) Acquire parameter sets and values of the first, second indexes thereof by repeating (c), (d). (f) Perform display based on the values of the first, second indexes with respect to two or more of the parameter sets. The value of the first index of the first parameter set is better than the value of the first index of the second parameter set. The value of the second index of the second parameter set is better than the value of the second index of the first parameter set.