Simulation-First Automation

By Daniel Patterson

 

Abstract

This paper presents the principle of simulation-first automation, a development methodology that advocates for constructing a fully functional digital twin before committing to physical system deployment. The approach significantly reduces costs, risks, and development time in industrial automation and motion control environments by relying on maturing 3D simulation, game engine, and digital design toolchains to prototype and validate automation workflows virtually. The paper critiques existing frameworks, particularly the Robot Operating System (ROS), for their disconnect from modern design paradigms, and offers a path forward that leverages mainstream design tools to democratize industrial automation development.

 

Introduction

The development and deployment of industrial automation systems have traditionally followed a hardware-first approach, where design, integration, and troubleshooting occur on live systems using physical components. This approach introduces tremendous cost, time, and logistical complexity, particularly for highly specialized or large-scale systems.

In contrast, the simulation-first methodology flips the process: it begins with the creation of a fully functional digital twin of the intended system. This virtual prototype not only models the geometry and behavior of physical components but also supports interaction, control logic, environmental inputs, and feedback pathways. Once the system is validated in the virtual environment, physical assembly proceeds using the tested simulation as a definitive blueprint, otherwise serving as a single source of truth.

 

The Case for Simulation-First Development

Industrial systems often involve an interplay of complex mechatronic components that may cost tens of thousands of dollars each. Mistakes in design or integration can lead to catastrophic budget overruns or operational failures. A simulation-first approach avoids these risks by validating every aspect of the system virtually before any physical component is purchased.

A simulation-first workflow benefits industrial automation teams in the following ways:

 

Cost-Free Experimentation

Virtual components can be instantiated and iterated upon without incurring hardware costs. A complete automation cell can be modeled using libraries of existing assets, from sensors and motors to conveyors and PLCs, with zero capital expenditure.

 

Rapid Iteration and Change Management

Modifications to layout, process timing, mechanical interlocks, and sensor logic can be tested instantly. Design changes that might require weeks of fabrication and procurement in the physical world take minutes in simulation.

 

Toolchain Compatibility and Accessibility

Most 3D design platforms now interoperate via common standards such as FBX, OBJ, GLTF, and USD. While not all tools are open-source, many free or community-supported platforms offer professional-grade functionality. This levels the playing field for smaller teams and independent developers.

 

Real-Time, Interactive Environments

Game engines such as Unity, Unreal Engine, and Godot provide robust, real-time environments optimized for physics-based interaction. These engines can simulate entire facilities with millisecond responsiveness, making them ideal for testing motion profiles, signal logic, and operator interfaces.

 

Protocol Transparency and Vendor Vetting

Building a functional simulation exposes limitations in vendor documentation early in the process. If a component lacks protocol transparency or cannot be modeled effectively due to poor specifications, this becomes apparent before any irreversible purchasing decisions are made.

 

The Cost of Skipping Simulation

In hardware-first workflows, surprises are expensive. Incompatibilities between components, mismatched protocols, or undocumented behaviors often surface only after significant investment. In contrast, simulation-first design can expose these issues early and virtually.

Complex systems, especially those spanning multiple control protocols and vendors, are notoriously prone to integration failures. By simulating the full data and control flow, down to the protocol and timing layers, teams can eliminate ambiguity and ensure cross-compatibility.

Additionally, the assumption that one can integrate all equipment around a popular protocol is often misguided. In the real world, components may lack the necessary interfaces or enforce proprietary integrations that derail original plans.

 

Shortcomings of ROS in the Simulation Era

The Robot Operating System (ROS) has become a default middleware choice for robotics development. While ROS provides a structured message-passing framework and has been instrumental in research, it falls short in several key areas when viewed through the lens of simulation-first design.

 

Steep Setup and Skill Barriers

ROS installations are notoriously fragile and require deep expertise in C++, Python, and Linux systems administration. There is little support for higher-abstraction interfaces such as visual scripting or natural language logic design.

 

Limited Platform Support

ROS works best on specific versions of Linux, with minimal or unreliable support for Windows or macOS. This restricts its accessibility and complicates cross-platform development.

 

Disconnect from Modern 3D Design

ROS formats like URDF and SDFormat are incompatible with mainstream 3D modeling standards and animation pipelines. This forces developers to maintain parallel definitions for visualization and control, doubling the effort and increasing the chance of error.

 

Overstated Capabilities

Although described as an operating system, ROS is fundamentally an event messaging bus. It lacks built-in support for physical control, kinematics, or feedback management without extensive user-side coding and third-party libraries.

Even recent improvements, such as O3DE’s native ROS support, still require developers to compromise on the familiar rigging and animation paradigms native to 3D software. Concepts like "bones" and "shape keys", standard in animation and game development, must be redefined or duplicated to satisfy ROS requirements, introducing unnecessary complexity.

 

What the Mainstream Design World Already Solves

Mainstream 3D tools and engines have evolved rapidly and now offer nearly every capability needed for effective digital twin creation and process validation.

 

Geometry Creation

Designers can sketch, extrude, sculpt, or Boolean model even complex assemblies using Blender, Fusion 360, or Rhino.

 

Rigging and Animation

Armatures (bones), constraints, inverse kinematics, and animation curves allow designers to simulate articulated systems and control loops with ease.

 

Materials and Physics

Game engines support dynamic lighting, collisions, rigid body dynamics, soft body simulation, and fluid interaction, all of which are critical for real-world process emulation.

 

Real-Time Logic and Communication

Through plugin architectures or custom scripting, these engines can send and receive messages via standard networking protocols (e.g., TCP/IP, MQTT, WebSockets), providing an ideal bridge to physical systems.

What is missing is not capability, but integration: a simple abstraction layer that translates in-game signals into packetized control messages for physical interfaces. This final step, developing or adopting lightweight, open messaging bridges, is far easier than forcing adoption of an overweight, aging, and incompatible framework.

 

Conclusion: A New Platform for Industrial Automation

Simulation-first automation empowers engineers to develop, iterate, and validate entire industrial systems without committing to hardware. This methodology aligns closely with modern software and game development practices, reduces development risk, and encourages innovation by making experimentation effectively free.

ROS, while foundational in robotics research, is out of sync with the direction of mainstream 3D development. The future lies in combining visual fidelity, real-time capability, and interactive design freedom of game engines with lightweight, open messaging interfaces that bridge to physical controllers.

The next-generation platform for automation will not emerge from specialized robotics frameworks alone, but from a thoughtful integration of tools that have already been widely adopted, democratizing development and unlocking creativity across domains.