Robotic Assembly Control for Moving Vehicle Line Variations
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Solution Overview
Problem
The challenge in automotive assembly is the movement irregularities and vibrations of vehicles on assembly lines, which hinder accurate modeling and repeatability of robot motion control, preventing the use of traditional teach and repeat position-based control systems during final trim and assembly operations.
Innovation Solution
A robotic assembly system that simulates operations to set and adjust control parameters, using sensor fusion and data analysis to determine suitable control schemes and parameters, allowing for stable assembly by compensating for movement irregularities and dynamic changes during production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional teach and repeat position based robot motion control is used, then the robot control system is simple and easy to operate, but the assembly operation cannot achieve stable repeatability due to vehicle movement irregularities and vibrations
Solution Approach 1:
The system continuously measures the actual position and orientation of the vehicle using sensors (laser scanners, cameras, GPS) and feeds this information back to the robot control system. This feedback loop enables real-time compensation for vehicle movement irregularities and vibrations, allowing the robot to maintain accurate positioning and achieve stable assembly repeatability despite the moving platform
Solution Approach 2:
The patent replaces traditional mechanical position-based control with a sensor-based measurement and computation system. Instead of relying on fixed mechanical positioning, the system uses laser scanners, cameras, and GPS receivers to measure vehicle position and orientation, then computes compensated robot motion commands to achieve accurate assembly operations on the moving vehicle
2Productivity
If the vehicle is transported continuously on a moving assembly line, then productivity is improved, but movement irregularities and vibrations prevent accurate modeling and prediction of part locations
Solution Approach 1:
The system performs preliminary measurement of the vehicle's position and orientation using sensors before the robot executes assembly operations. This advance measurement allows the control system to predict part locations and pre-compute compensated robot motion commands, ensuring accurate assembly even as the vehicle moves continuously through the production line
Solution Approach 2:
The patent replaces mechanical positioning assumptions with optical and electromagnetic sensing systems. Laser scanners, cameras, and GPS receivers continuously measure the vehicle's actual position and orientation, replacing the need for precise mechanical positioning. This substitution enables accurate part location determination despite continuous vehicle movement on the assembly line
3Adaptability or versatility
If control parameters are manually tuned during setup, then the system can adapt to specific conditions, but the setup time and complexity increase significantly
Solution Approach 1:
The system automatically determines optimal control parameters through simulation and self-testing during setup. The robot control system performs dry runs with test parameters, evaluates assembly accuracy and repeatability, and automatically adjusts parameters without requiring extensive manual tuning by operators. This self-service capability reduces setup time while maintaining adaptability to specific assembly conditions
Solution Approach 2:
The system performs preliminary simulation and parameter optimization during the setup phase before production begins. By pre-determining optimal control parameters through virtual testing and dry runs, the system eliminates the need for time-consuming manual parameter tuning during actual production, achieving both adaptability and efficiency
Data Source
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AI summary
A robotic assembly operation is provided for assembling a second part to a first part. During setup of the assembly operation, control parameters and a control scheme are set and changed by simulating the operation and testing whether performance requirements are met. A dry run may be performed thereafter, and test data may be collected after running the simulation to determine if the performance requirements are satisfied during the dry run. During production, production data may also be collected and control parameters may be tuned when changes occur during production in order to maintain stable assembly.