Robot Process Modeling for Vendor-Neutral Automation Programming
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Solution Overview
Problem
The programming of industrial robots is complex, costly, and inflexible, making automation unattractive for small and medium-sized enterprises, and the low degree of flexibility is also unattractive for large enterprises, with conventional methods requiring expert intervention and being time-consuming for conversions.
Innovation Solution
A method that creates a machine-independent process model from data representing the handling of a work tool during a process flow, which is then mapped onto a machine-specific control model to generate a control program, enabling automation by a technical layman.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional expert programming is used, then programming precision and reliability are improved, but device complexity and loss of time increase
Solution Approach 1:
The system creates a digital twin (virtual model) of the physical robot system that can be programmed and simulated independently. This virtual model copies the essential behaviors and interfaces of the real robot, allowing programmers to develop and test code without physically manipulating the actual robot, thereby reducing programming time while maintaining reliability through virtual validation before deployment to the physical system.
Solution Approach 2:
The system performs preliminary programming and validation in the virtual environment before deploying to the physical robot. All complex programming tasks, including movement planning, tool integration, and process logic, are completed in advance in the virtual model, allowing the physical robot to simply execute pre-validated code, significantly reducing on-site programming time while ensuring reliability through prior virtual testing.
2Manufacturing precision
If conventional expert programming is used, then programming precision is improved, but ease of operation deteriorates
Solution Approach 1:
The virtual model serves as an intermediary layer between the programmer and the physical robot system. It provides a simplified, intuitive interface for programming while maintaining precise control over the complex robot hardware. The virtual model translates high-level programming instructions into detailed robot control commands, making the system accessible to less experienced programmers while preserving programming precision through the structured virtual environment.
Solution Approach 2:
By creating a virtual copy of the robot system, the invention provides a safe, accessible environment where programmers can learn and experiment without risking damage to expensive physical equipment. The virtual model replicates all essential robot functions and interfaces, allowing programmers to develop skills and create programs with the same precision as conventional methods, while significantly improving accessibility to robot programming.
3Manufacturing precision
If vendor-specific programming is used, then manufacturing precision is improved, but adaptability deteriorates
Solution Approach 1:
The virtual model provides a universal programming interface that can control different robot vendors and models through standardized communication protocols. It acts as a vendor-neutral layer that translates universal programming instructions into vendor-specific commands, maintaining precise process control through the structured virtual environment while enabling adaptability to different hardware platforms without requiring vendor-specific programming expertise.
Solution Approach 2:
The virtual model serves as a mediator between the universal programming interface and vendor-specific robot hardware. It maintains precise process control through its structured internal representation while providing adaptability by translating commands to work with different robot vendors, eliminating vendor lock-in while preserving manufacturing precision through the consistent virtual execution environment.
4Ease of operation
If teaching method is used, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The system creates a virtual copy of the teaching process where simple trajectory recording in the virtual model automatically generates complete control programs including all complex integrations. The virtual model captures the essential teaching actions (movement recording, tool operations) and automatically expands them into comprehensive control code that handles sensor integration, process logic, and coordination, maintaining ease of operation through simple virtual teaching while managing device complexity through automated code generation.
Data Source
AI summary
Disclosed herein is a method, system, and non-volatile storage medium for simplifying the automation of a process of flow. The method may include determining a machine-independent process model based on data representing a handling of a work tool for performing a process flow. The process flow may include a plurality of sub-processes and the process model may link a process activity with spatial information for each sub-process. The method may also include mapping the machine-independent process model to a machine-specific control model of a machine using a model of the machine. The machine-specific control model may define an operating point of the machine for each sub-process, and the operating point may correspond to the process activity and to the spatial information.