Fixtureless Robot Pickup Using Virtual Datums for Sheet Metal Assembly
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Solution Overview
Problem
The high costs and obsolescence of dedicated hardware fixtures in manufacturing, particularly in the automotive industry, due to the complexity of design and frequent product changes, necessitate a more flexible and cost-effective solution for securing and locating sheet metal parts during welding processes.
Innovation Solution
A reconfigurable, fixtureless manufacturing system utilizing learning AI software and material handling robots with machine vision systems to create virtual datums, allowing for the secure handling and joining of differently shaped and sized parts without physical fixtures, enabling optimization through multiple production iterations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If dedicated hardware fixtures are used to secure and locate sheet metal parts for welding, then manufacturing precision and stability are improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent replaces the mechanical fixture system with a robotic manipulation system equipped with sensors and control algorithms. Robots with specialized end effectors grasp and position parts without physical fixtures, while sensors detect part locations and the control system calculates optimal grasping strategies to achieve precise positioning through software rather than mechanical means.
Solution Approach 2:
The patent creates virtual models and digital twins of physical fixtures and parts in the control system. These digital representations allow the system to simulate and optimize grasping strategies, predict part behavior during manipulation, and reproduce precise positioning without requiring physical fixture copies for each configuration.
2Manufacturing precision
If dedicated hardware fixtures are designed and manufactured for each subassembly, then manufacturing precision is improved, but loss of time and adaptability worsen due to frequent redesigns
Solution Approach 1:
The patent implements a dynamic, reconfigurable robotic system that can adapt its manipulation strategy in real-time. The control system continuously receives sensor data about part variations and dynamically adjusts grasping forces, robot trajectories, and positioning calculations to maintain precision without requiring physical reconfiguration or redesign of fixtures for each assembly variation.
Solution Approach 2:
The patent changes the control parameters and software algorithms rather than physical fixture parameters when assembly requirements change. The system modifies grasping forces, robot motion parameters, sensor thresholds, and positioning calculations through software updates, allowing rapid adaptation to new subassemblies without time-consuming physical redesign and manufacturing of new fixtures.
3Adaptability or versatility
If flexible fixture systems are used to accommodate product changes, then adaptability is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The patent employs universal robotic manipulators with interchangeable end effectors that can handle multiple part types and assembly configurations. A single robotic system performs the functions of multiple dedicated fixtures by programmatically adapting its grasping and positioning strategies, eliminating the need for complex flexible fixture systems while maintaining versatility across different products and assemblies.
Solution Approach 2:
The patent replaces the mechanical flexibility of adjustable fixtures with software-based adaptability. The robotic control system uses sensors, algorithms, and real-time calculations to accommodate part variations and assembly requirements, substituting mechanical complexity with computational intelligence to achieve flexibility without physical reconfiguration mechanisms.
4Productivity
If robots and automated assembly systems with physical fixtures are used, then productivity is improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts and removes the physical fixture component from the automated assembly system, retaining only the robotic manipulation and control functions. By taking out the complex mechanical fixture subsystem while keeping the productive robotic assembly capabilities, the system maintains high productivity with reduced complexity and cost.
Solution Approach 2:
The patent uses virtual models and digital representations of fixtures and assembly targets to guide robotic manipulation. The control system creates and uses digital twins of the assembly environment, allowing robots to achieve precise positioning and high productivity through software guidance rather than complex physical fixture systems.
Data Source
AI summary
Systems and methods for learning software assisted, fixtureless object pickup and placement include a controller which derives measured target points from image(s) of a part in a work area received from a machine vision system, performs an iterative analysis to determine a best fit solution for moving the part adjacent to another part for forming the assembly such that each of the measured target points is within a predetermined range of an associated one of desired target points for said part, where the other part is located at support object(s). The controller converts the measured target points to a common reference frame and command movement of the part, by way of the robot, according to said best fit solution as converted such that the part is moved and secured adjacent to the other part in a fixtureless manner.