Fixtureless Robotic Assembly Using Transformation Matrix Correction
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Solution Overview
Problem
Existing robotic assembly systems face challenges in accurately positioning robotic arms during assembly operations, particularly when dealing with complex structures and tight tolerance thresholds, which can lead to inaccuracies and reduced precision in the assembly process.
Innovation Solution
The system employs a method where a control unit calculates and measures the location of features on subcomponents, determines a transformation matrix between calculated and measured locations, and repositions the features using robotic arms based on this matrix, ensuring precise alignment and assembly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional robotic assembly systems are used, then automation is achieved, but positioning precision deteriorates due to accumulated errors and lack of real-time correction
Solution Approach 1:
The system implements real-time feedback by measuring the actual positions of features on subcomponents during assembly and using this information to dynamically adjust robotic arm positioning. Sensors capture position data, which is fed back to the control system to correct deviations from the planned trajectory, thereby maintaining high positioning precision throughout the assembly process.
Solution Approach 2:
The patent replaces traditional mechanical positioning systems with a sensor-based measurement and computation system. Instead of relying on mechanical fixtures and pre-calibrated robotic paths, the system uses sensors to measure actual feature positions and computational algorithms to determine corrective transformations, substituting mechanical precision requirements with sensor measurement and digital correction.
2Adaptability or versatility
If fixed fixtures are used for assembly, then positioning accuracy is maintained, but adaptability to different components deteriorates
Solution Approach 1:
The system transitions from static fixed fixtures to dynamic adaptive positioning. The robotic arms can adjust their positions in real-time based on measured feature locations, and the transformation matrices are computed dynamically for each assembly operation. This allows the same system to adapt to different subcomponent geometries and tolerances while maintaining assembly accuracy.
Solution Approach 2:
The system changes the parameters of the robotic positioning system based on measured data. Transformation matrices are computed that map between the coordinate systems of different subcomponents, and these parameters are adjusted in real-time based on actual feature positions. This allows the system to accommodate variations in component manufacturing while maintaining precise assembly.
3Manufacturing precision
If multiple measurement and correction steps are implemented, then positioning accuracy improves, but assembly time increases
Solution Approach 1:
The system performs preliminary measurements of feature positions before the actual assembly operation. By measuring and computing transformation matrices in advance, the system prepares the correction data needed for high-speed assembly execution. This preliminary action allows the robotic arms to move quickly along pre-computed corrected trajectories without real-time measurement delays during the critical assembly moment.
Data Source
AI summary
An approach to positioning one or more robotic arms in an assembly system may be described herein. For example, a system for robotic assembly may include a first robot, a second robot, and a control unit. The control unit may be configured to receive a first target location proximal to a second target location. The locations may indicate where the robots are to position the features. The control unit may be configured to calculate a first calculated location of the first feature of the first subcomponent, measure a first measured location of the first feature of the first subcomponent, determine a first transformation matrix between the first calculated location and the first measured location, reposition the first feature of the first subcomponent to the first target location using the first robot, the repositioning based on the first transformation matrix.