Algoryx | Control System Development

Use high-fidelity machine simulation to test control policies, from task planning to low-level controllers.

CHALLENGE:

Control Logic Needs a Realistic Machine Model to Act On

Control system development tends to start from simplified models, idealized assumptions, and software-in-the-loop environments that only partially represent the full detail and complexity of the real machine.

This becomes a weak foundation when machines operate in unstructured environments where motion, contact, loads, terrain and actuator response all shape the result.

As control systems move beyond classical control loops to full-fledged autonomy stacks, developing policies and control strategies against the behavior of the full machine becomes all the more critical.

Engineers need to test control strategies in closed loop, expose autonomy policies to realistic operating conditions, and explore failure modes before they reach physical testing.

SOLUTION:

Test Control Systems Against Realistic Machine Dynamics in Simulation

Start with a physics-based machine model

Use a simulation-ready machine model that represents machine dynamics, terrain interaction and relevant operating conditions.

Connect external control or planning logic

Command the simulated machine from controllers, planners or autonomy software through supported integration workflows such as ROS 2, Python or other system interfaces.

Run Closed-Loop Scenarios

Apply control inputs, observe machine response and evaluate behaviour under realistic loads, terrain conditions and environmental variation.

Compare, refine and validate strategies

Test parameter changes, edge cases and control strategies in repeatable simulations before moving to physical machines.

VIDEO:

See How it Works

KEY FEATURES:

Key Capabilities for Closed-Loop Control Simulation

High-Fidelity Plant Model for Control Development

AGX Dynamics is powering the physics-based plant model in closed-loop control setups, simulating full-system machine dynamics, contacts, constraints, actuators and mechanical coupling in real time.

Terrain and Material Interaction in the Control Loop

Algoryx supports simulation of interaction with terrain and materials such as soil, gravel and bulk media, allowing resistance, deformation and load transfer to influence machine behaviour in a physically realistic way.

Flexible Integration With Your Control Stack

Use AGX with established control and simulation workflows, including ROS 2, Python APIs, Matlab/Simulink co-simulation and FMI export, to evaluate control logic against a physics-based machine model.

RELATED USE CASES:

Digital Twins

Create and simulate physics-based full-system models of machines and vehicles

Sensor Simulation

Understand sensor behaviour in realistic work scenarios.

Synthetic Data and AI Training

Generate synthetic training data for training neural networks and developing autonomy.

Simulation at Scale

Scale up and batch simulations, in the cloud or locally.

FAQ:

Frequently asked questions

Why use physics-based simulation for control development?

Control performance is strongly affected by machine dynamics, contacts, actuator response, loads and interaction with terrain or materials. Physics-based simulation lets engineering teams evaluate control behaviour under these conditions before relying on physical machine tests alone.

For off-road machines and field robotics, this is especially important because resistance, deformation, load transfer and machine–terrain interaction can materially change how a control strategy performs.

What types of machines and machine components can be simulated and controlled in Algoryx’s software?

AGX Dynamics is built on general-purpose multibody dynamics simulation, making it adaptable across a wide range of industries and application areas – from heavy machines, cranes and vehicles to indudtrial robots, humanoids, ships and material handling equipment. Our deepest expertise lies in terrain interaction, earthmoving and complex material behaviour, supported by unique modelling capabilities for tracks, tires, drivetrains, hydraulics, cables, wires, actuators, terrain, bulk materials, and more.

How can we integrate our existing control system with Algoryx’s simulation solutions?

Algoryx solutions are designed to support integration with external control and planning workflows. Common integration paths include ROS 2, Python APIs, Matlab/Simulink co-simulation and FMI export, depending on the customer’s existing tools and simulation requirements. In this type of setup, AGX Dynamics provides the physics-based machine model and simulation runtime, while the customer’s control logic can be connected to command the simulated machine and evaluate its response.

Why is the simulation-to-reality gap so hard to bridge for off-road machines?

Off-road machines operate in conditions that are difficult to simplify without losing important behaviour. Terrain and materials such as soil, gravel and bulk media can deform, resist motion and change under load. This affects traction, stability, digging, grading, braking and other machine behaviours.

A simplified model may be useful for early design work, but control development often requires a more representative simulation of the full machine and its interaction with the environment.

Ready to get in touch?

Contact our sales team and book a discovery call to explore how Algoryx can help you achieve engineering success.

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