Assembly Robot Offset Control for Part Pose Accuracy
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Solution Overview
Problem
Existing assembly processes face challenges in maintaining precision due to part variations, mechanical tolerances, and misalignment between robot and vehicle coordinate systems, leading to deviations in the pose of assembled parts.
Innovation Solution
A method and control unit that determine deviation data at multiple measurement points, calculate offset data using a transformation matrix, and adjust robot operations to reduce these deviations, ensuring parts are assembled within a specified tolerance band.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If robot assembly operations are performed using standard mechanical tolerances, then the assembly process can proceed at normal speed, but the pose of assembled parts drifts away from target pose over time due to cumulative errors
Solution Approach 1:
The system performs preliminary measurement of the actual pose of assembled parts using measurement devices (e.g., laser scanners, cameras) before the assembly operation is complete. This allows the system to calculate offset data and adjust robot operations in advance for subsequent parts, preventing pose drift rather than correcting it after the fact.
Solution Approach 2:
The system implements a closed-loop feedback mechanism where measurement data from previously assembled parts is fed back to adjust the robot's assembly operations. The control unit calculates offset data based on measured deviations and uses this feedback to modify the pose and positioning of subsequent parts, ensuring continuous precision throughout the assembly process.
2Measurement precision
If multiple measurement points are used to determine deviation data, then the precision of pose measurement increases, but the complexity of the measurement and calculation process increases
Solution Approach 1:
The measurement process is segmented into discrete measurement points distributed across the surface of assembled parts. Each measurement point provides localized deviation data, and the control unit processes these segmented measurements individually to calculate overall pose offsets. This segmentation allows for comprehensive coverage without requiring a single complex measurement system.
Solution Approach 2:
The control unit acts as an intermediary that receives raw measurement data from multiple measurement points, processes this data through transformation matrices, and converts it into actionable offset data for robot adjustment. This intermediary processing layer simplifies the overall system by centralizing the complexity of multi-point measurement analysis in a dedicated computational unit.
3Manufacturing precision
If offset data is calculated and used to adjust robot operations, then assembly precision is improved, but the complexity of the control process increases
Solution Approach 1:
The system dynamically changes the operational parameters of the robot based on calculated offset data. Instead of modifying the physical robot hardware, the control unit adjusts parameters such as pose coordinates, positioning offsets, and transformation matrices. This allows for precise control adjustments without increasing mechanical complexity.
Solution Approach 2:
The system creates a digital model or representation of the offset data and uses this copied information to adjust robot operations. The transformation matrices and offset values serve as digital copies of the physical deviations, allowing the control unit to simulate and apply corrections in the virtual space before executing them physically, thereby simplifying the control process.
Data Source
Figure 1a~1c
Figure 2
AI summary
A method (200) for controlling an assembly step of a part (105) onto a body (101) of a product (100), which is performed by a robot (110). The method (200) comprises determining (201) deviation data at a plurality of measurement points (132) of an already assembled part (105), wherein the deviation data indicates for each measurement point (132) a deviation in a measurement direction (131) from a target position of the measurement point (132). Furthermore, the method (200) comprises determining (202) offset data based on the deviation data and based on a transformation matrix for the plurality of measurement points (133) and the plurality of measurement directions (131). In addition, the method (200) comprises adjusting (203) operation of the robot (110) for assembling a subsequent part (105) based on the offset data, in order to reduce the deviation for at least one of the measurement points (132).