Robot Cable Motion Simulation Using AI for Failure Prevention
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Solution Overview
Problem
Existing robotic operations face downtime due to cable failures, which are not adequately addressed in real-time simulations, leading to inefficient and potentially damaging robotic processes.
Innovation Solution
Utilizing artificial intelligence to determine cable positions and risks of failure by simulating kinematic systems without directly modeling cable mechanics, allowing real-time prediction and prevention of cable failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional cable simulation methods are used, then cable movement can be simulated, but the simulation is too slow for real-time robot process simulations
Solution Approach 1:
The patent replaces traditional mechanical cable simulation methods with an artificial intelligence-based approach. The AI model learns cable behavior patterns from training data and predicts cable positions in real-time during robot simulations, eliminating the need for computationally intensive physical cable simulations while maintaining accuracy for failure prevention
Solution Approach 2:
The patent performs preliminary training of the AI model using extensive cable simulation data before real-time operation. This preliminary action creates a pre-trained model that can quickly predict cable positions during actual robot simulations, resolving the speed-accuracy tradeoff by doing the heavy computational work beforehand
Data Source
AI summary
A system and a method simulate a motion of a cable of a real kinematic system, e.g. robot, containing one or several joints. The method includes the following steps: receiving a virtual representation of the real kinematic system; receiving a target task to be performed by the real kinematic system; perform the target task, and the simulation is configured for calculating a next joint value from a previous joint value. The method is characterized in that each simulation time interval results in a calculation of a next joint value from a previous joint value, and the next joint value is used as an input to a cable position artificial intelligence algorithm trained for outputting a cable position for the next joint value. The outputted cable position for the next joint value is stored.