本文章目前仅提供英文版本。InSystems与Model Engineering Solutions（MES模赛思）联合为一套自适应运输机器人编队开发了一个Simulink模型。该车队基于InSystems的proANT机器人。其目标是准确呈现自适应系统行为，并有效应对协作式嵌入式系统群组（Collaborative Embedded System Groups，CSGs）的典型挑战。
本文先前刊载于Robotic Magazine。
使用Simulink对运输机器人编队进行建模
In modern manufacturing environments, the interaction of multiple autonomous robots must be both flexible and robust. Production lines need to respond quickly to changing order priorities, fluctuating volumes, or the failure of individual robots - without compromising overall efficiency.
To achieve this level of adaptability and robustness, InSystems and Model Engineering Solutions developed a Simulink model of a fleet of proANT collaborative transport robots. The model represents the behavior of a Collaborative Embedded System Group (CSG) and serves as the foundation for the complete model-based development (Model-Based Development, MBD) of the automation solution.
Challenges in Collaborative System Groups (CSG)
A robot fleet must continuously respond to dynamic changes. These include adjustments in the control logic of the manufacturing execution system as well as changes in the number and characteristics of participating systems.
This dynamic behavior increases complexity in both development and operation. Traditional development approaches quickly reach their limits, particularly in terms of traceability, testability, and scalability.
Solution Approach: Model-Driven Software Development (MDSD / MDD)
Model-Driven Software Development (MDSD / MDD) provides a structured approach to managing this complexity.
By specifying the CSG as executable models, a fully virtual and simulated representation of the robot fleet is created. This enables early analysis, validation, and targeted optimization of system behavior.
Key benefits include:
- Early virtual verification in initial development phases
- Faster iteration cycles through simulation
- Reduced implementation risks
- Improved maintainability and scalability
Reusability as an Efficiency Driver
A key advantage of model-based development is the reuse of models and test environments across different development phases. Once created, components can be leveraged throughout the lifecycle.
This results in:
- Reduced development effort
- Consistent system architecture
- Higher quality through standardized components
Especially in complex, adaptive systems, reusability is a critical factor for long-term project success.
Integrated Toolchain and Automated Quality Assurance
Another success factor is the seamless integration of the toolchain, enabling a high degree of automation in core development activities:
- Requirements management
- Modeling and simulation
- Static model analysis
- Requirements-based testing
Quality assurance in particular benefits from model-based approaches. Tools such as the MES Model Examiner® (MXAM) help ensure compliance with modeling guidelines, analyze model structures, and evaluate relevant model metrics.
From Modeling to Reliable System Development
The combination of modeling, simulation, and automated analysis provides a solid foundation for developing adaptive robotic systems. Changes in system behavior can be evaluated early and implemented efficiently.
This not only reduces development time but also leads to sustainable improvements in system quality.
Learn More from Our Experts
MXAM in Action
MES Model Examiner® (MXAM) provides a convenient all-in-one solution for checking modeling guidelines, analyzing model structure, and evaluating model metrics. In this webinar, we explored how MXAM supports comprehensive static analysis for models created with Simulink, Stateflow, Embedded Coder, and TargetLink.
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