External PC Optimizes Robot Control Parameters
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Solution Overview
Problem
Existing robot control programs are not optimized in real-time for varying robot systems and operating conditions, leading to performance variations and instability, and lack integration of essential motor current feedback and dynamic parameter adjustments.
Innovation Solution
A method and apparatus that utilize an external PC as a secondary processor to analyze and optimize robot paths and control parameters in real-time, incorporating motor current feedback and dynamic modeling to iteratively adjust system parameters and robot programs, ensuring stability and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If robot control programs are optimized offline independently of the robot system, then program development is simpler, but performance variations occur when executed on different robots and operating conditions
Solution Approach 1:
The system implements real-time feedback by monitoring actual robot execution performance and using this data to iteratively optimize control parameters. The external processor receives performance data from the robot controller, analyzes the discrepancies between planned and actual performance, and adjusts parameters accordingly, creating a closed-loop optimization system that adapts to specific robot hardware and operating conditions.
Solution Approach 2:
The optimization system transitions from static offline program development to dynamic real-time optimization. The control parameters are no longer fixed but are continuously adjusted based on actual robot performance data, allowing the system to adapt to variations in different robot models and operating conditions while maintaining performance consistency.
2Reliability
If real-time optimization is implemented using the robot controller's main CPU, then performance consistency improves, but processing speed and other tasks suffer due to excessive CPU load
Solution Approach 1:
The system segments the optimization function from the main robot controller by introducing an external processor. The robot controller focuses on real-time control execution while the external processor handles the computationally intensive optimization calculations. This segmentation allows real-time optimization without burdening the main CPU, maintaining both performance consistency and processing speed.
Solution Approach 2:
An external processor acts as an intermediary between the robot controller and the optimization algorithm. This intermediary receives performance data from the controller, performs the optimization calculations, and sends adjusted parameters back to the controller, enabling real-time optimization without directly loading the robot controller's CPU.
3Adaptability or versatility
If optimization iterates on an interval-by-interval basis with servo system state changes, then real-time adaptation occurs, but instability and slow conversion process result
Solution Approach 1:
The system performs preliminary optimization calculations during idle periods or between robot operations, preparing optimized parameters in advance. This allows the system to implement stability checks and validate parameter changes before applying them to the running robot system, reducing instability risks while maintaining real-time adaptation capability.
4Adaptability or versatility
If motor current feedback and dynamic parameter adjustments are integrated, then optimization comprehensiveness improves, but system complexity increases
Solution Approach 1:
The external processor serves multiple functions: it monitors motor current feedback, analyzes performance data, calculates optimized parameters, and communicates with the robot controller. This multi-functionality consolidates the complexity into a single external device rather than requiring multiple separate systems, making the comprehensive optimization approach more manageable and scalable.
Data Source
AI summary
An apparatus and a method for optimizing robot performance includes a computer connected to the robot controller for receiving performance data of the robot as the controller executes a path program. The computer uses the performance data, user specified optimization objectives and constraints and a kinematic/dynamic simulator to generate a new set of control system parameters to replace the default set in the controller. The computer repeats the process until the new set of control system parameters is optimized.