Optimizing Robotic Joint Configurations for Energy and Cycle Time
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Solution Overview
Problem
Industrial robots consume significant energy and have long cycle times due to inefficient joint configurations, which are not effectively optimized in existing systems, leading to increased production costs.
Innovation Solution
A method that involves simulating robotic joint configurations, calculating edge ratings for robotic movements, determining candidate configuration paths, and identifying the optimal configuration path with the lowest rating to minimize energy consumption and cycle time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If traditional robotic joint configurations are used, then the robot can complete tasks, but energy consumption is high and cycle time is long
Solution Approach 1:
The patent changes the parameters of joint configurations by evaluating multiple possible configurations at each task location and selecting the optimal sequence. The system calculates edge ratings based on energy consumption and cycle time parameters, then determines the configuration path with the lowest total rating, thereby optimizing both energy usage and productivity simultaneously.
Solution Approach 2:
The patent introduces dynamic optimization by evaluating joint configurations in real-time based on the robot's current state and task requirements. The system dynamically selects from multiple candidate configurations at each location, adapting the joint settings to minimize energy consumption and cycle time rather than using fixed predetermined configurations.
2Loss of energy
If multiple joint configurations are evaluated to find optimal paths, then energy consumption and cycle time are reduced, but computational complexity increases
Solution Approach 1:
The patent segments the complex optimization problem into smaller manageable components by evaluating joint configurations at each individual task location separately. The system divides the overall path into discrete edges between locations, calculating edge ratings for each segment independently, then combines these to determine the optimal complete path. This segmentation reduces computational complexity compared to evaluating all possible paths simultaneously.
Solution Approach 2:
The patent uses simulated robot models to copy and evaluate multiple joint configurations virtually before implementing the optimal configuration. The simulation creates virtual copies of the robot in different configurations, allowing the system to assess energy consumption and cycle time for each candidate path without physical trial and error, thereby reducing computational burden.
Data Source
AI summary
Methods for saving energy and reducing cycle time of a complex operation by using optimal robotic joint configurations. A method includes receiving inputs including the complex operation, generating a plurality of joint configurations of a simulated robot for each one of a plurality of task locations based on the inputs of the complex operation, calculating an edge rating for each of a plurality of robotic movements, wherein a robotic movement accounts for movement between joint configurations of consecutive task locations, calculating a plurality of candidate ratings for each of a plurality of candidate configuration paths, wherein a candidate rating is a summation of edge ratings of robotic movements for a candidate configuration path, determining an optimal configuration path based the candidate configuration path with an optimal rating, wherein the optimal rating is determined by the lowest candidate rating, and return the optimal configuration path.