[Skip to main content](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/04-bridging-the-gap-real-world-data-integration/01-actuator-modeling.html.md#main-content) Back to top Ctrl+K [Getting Started With Isaac Lab](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/index.html.md) Choose version Search Ctrl+K - [YouTube](https://www.youtube.com/@NVIDIAOmniverse) - [Discord](https://discord.gg/nvidiaomniverse.md) - [Survey](https://surveys.hotjar.com/98510484-7ad7-4ddc-bfc4-1b7663827216.md?utm_source=getting-started-with-isaac-lab) - [Home](https://docs.nvidia.com/learning/physical-ai/) Search Ctrl+K [Getting Started With Isaac Lab](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/index.html.md) Choose version - [YouTube](https://www.youtube.com/@NVIDIAOmniverse) - [Discord](https://discord.gg/nvidiaomniverse.md) - [Survey](https://surveys.hotjar.com/98510484-7ad7-4ddc-bfc4-1b7663827216.md?utm_source=getting-started-with-isaac-lab) - [Home](https://docs.nvidia.com/learning/physical-ai/) Table of Contents Contents - [Robot Learning Fundamentals](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/robot-learning-fundamentals/index.html.md) - [Motivation and Definition](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/robot-learning-fundamentals/01-motivation-and-definition.html.md) - [Problem Specification](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/robot-learning-fundamentals/02-problem-specification.html.md) - [Forms of Learning](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/robot-learning-fundamentals/03-forms-of-learning.html.md) - [Reinforcement Learning](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/robot-learning-fundamentals/04-reinforcement-learning.html.md) - [Proximal Policy Optimization](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/robot-learning-fundamentals/05-proximal-policy-optimization.html.md) - [Reward Design and Evaluation](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/robot-learning-fundamentals/06-reward-design-and-policy-evaluation.html.md) - [Policy Distillation](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/robot-learning-fundamentals/07-policy-distillation.html.md) - [Simulation to Reality](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/robot-learning-fundamentals/08-simulation-to-reality.html.md) - [Robot Learning Workflows](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/robot-learning-fundamentals/09-robot-learning-workflows.html.md) - [Isaac Lab Basics](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/isaac-lab-basics/index.html.md) - [The Isaac Platform](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/isaac-lab-basics/01-the-isaac-platform.html.md) - [Project Generation](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/isaac-lab-basics/02-isaac-lab-projects.html.md) - [Development Workflow](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/isaac-lab-basics/03-development-workflow.html.md) - [The Isaac Lab CLI](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/isaac-lab-basics/04-isaac-lab-cli.html.md) - [Manager-Based Workflows](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/isaac-lab-basics/05-manager-based-workflows.html.md) - [The Cartpole Example](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/isaac-lab-basics/06-isaac-lab-cartpole.html.md) - [Cartpole Training](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/isaac-lab-basics/07-cartpole-training.html.md) - [Train a Robot Arm](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/train-a-robot-arm/index.html.md) - [Project Setup](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/train-a-robot-arm/01-project-setup.html.md) - [SO-101 Robot](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/train-a-robot-arm/02-so101-robot.html.md) - [Vial and Rack Scene](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/train-a-robot-arm/03-vial-and-rack.html.md) - [Running Simple Agents](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/train-a-robot-arm/04-simple-agents.html.md) - [Train a Teacher Policy](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/train-a-robot-arm/05-teacher-policy.html.md) - [Distill a Student Policy](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/train-a-robot-arm/06-distilled-policy.html.md) - [Managing Experiments](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/train-a-robot-arm/07-managing-experiments.html.md) - [Transfer Policies From Simulation to Reality](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/index.html.md) - [Overview](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/index.html.md) - [The Successes of Reinforcement Learning](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/01-reinforcement-learning/index.html.md) - [Reinforcement Learning](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/01-reinforcement-learning/index.html.md) - [The Challenges of Reinforcement Learning](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/01-reinforcement-learning/01-the-challenges-of-reinforcement-learning.html.md) - [Simulation: A Game-Changer](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/01-reinforcement-learning/02-simulation.html.md) - [What Is the Reality Gap?](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/02-the-reality-gap/index.html.md) - [The Reality Gap](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/02-the-reality-gap/index.html.md) - [Visualizing the Reality Gap](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/02-the-reality-gap/01-visualizing-the-reality-gap.html.md) - [Bridging the Gap: Simulation Enhancement](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/03-bridging-the-gap-simulation-enhancement/index.html.md) - [Domain Randomization](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/03-bridging-the-gap-simulation-enhancement/index.html.md) - [Visual Domain Randomization](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/03-bridging-the-gap-simulation-enhancement/01-visual-domain-randomization.html.md) - [Depth Camera Randomization](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/03-bridging-the-gap-simulation-enhancement/02-depth-camera-randomization.html.md) - [Point Cloud Perturbations](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/03-bridging-the-gap-simulation-enhancement/03-point-cloud-perturbations.html.md) - [Bridging the Gap: Real-World Data Integration](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/04-bridging-the-gap-real-world-data-integration/index.html.md) - [System Identification](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/04-bridging-the-gap-real-world-data-integration/index.html.md) - [Actuator Modeling](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/04-bridging-the-gap-real-world-data-integration/01-actuator-modeling.html.md#) - [Digital Twins](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/04-bridging-the-gap-real-world-data-integration/02-digital-twins.html.md) - [Neural Rendering](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/04-bridging-the-gap-real-world-data-integration/03-neural-rendering.html.md) - [World Models](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/04-bridging-the-gap-real-world-data-integration/04-world-models.html.md) - [Regularization](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/05-bridging-the-gap-policy-robustness/index.html.md) - [Regularization](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/05-bridging-the-gap-policy-robustness/index.html.md) - [Leveraging Privileged Information](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/05-bridging-the-gap-policy-robustness/01-leveraging-privileged-information.html.md) - [Considerations When Bridging the Reality Gap](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/06-conclusion/index.html.md) - [Considerations](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/06-conclusion/index.html.md) - [Tips for Sim-to-Real](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/06-conclusion/01-tips-for-sim-to-real.html.md) - [Review](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/06-conclusion/02-review.html.md) - [Quiz](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/06-conclusion/03-quiz.html.md) Resources [Physical AI Learning Hub](https://docs.nvidia.com/learning/physical-ai/) [Developer Forums](https://forums.developer.nvidia.com/c/omniverse/300) [Community Discord](https://discord.gg/nvidiaomniverse.md) - [Home](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/index.html.md) - [Transfer Policies From Simulation to Reality](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/index.html.md) - [Bridging the Gap: Real-World Data Integration](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/04-bridging-the-gap-real-world-data-integration/index.html.md) - Actuator Modeling # Actuator Modeling[#](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/04-bridging-the-gap-real-world-data-integration/01-actuator-modeling.html.md#actuator-modeling 'Link to this heading') Actuator modeling is another interesting topic in real-to-sim. In Isaac Lab, we use what we call actuator networks to replicate the behavior of real actuators on robots. These networks play a key role in bridging the gap between simulation and reality. Let’s talk about why this is important. Actuators on robots are complex systems. Series elastic actuators, for example, have a motor, a harmonic drive, and a spring all working together in series. It’s incredibly difficult to model this accurately using traditional methods. So, here’s what we do instead. We gather a bunch of input-output data from the actual robot’s actuators. The input includes the command given to the motor and the history of joint states up to that point. The output will be the actual joint torques, which can be measured accurately by measuring the deflection of the spring (Hooke’s Law). Using this data, we train a neural network that captures the input-output behavior of the actuators. This approach lets us bypass all the complexity of the physical system. It can even account for system delays because we’re measuring from the moment the command is sent from the computer to when the torque is measured on the robot. Typically robots in simulation use a proportional-integral-derivative (PID) controller to compute the torque applied on each actuator. With actuator modeling, we bypass this and instead use the trained actuator network to compute which torque is applied on each joint at any point in time. The actuator network is frozen when deployed in simulation, meaning it is not trained further and the weights are not updated. How is this data collected? We send random commands to the motors, trying to excite the robot in all its possible modes of operation. This helps us gather a comprehensive dataset for training the network later on. By using these actuator networks, we can create more accurate simulations that better reflect the behavior of real-world robots. This is a crucial step in developing robotic systems that can seamlessly transition from simulation to reality. [previous\\ \\ Bridging the Gap: Real-World Data Integration](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/04-bridging-the-gap-real-world-data-integration/index.html 'previous page') [next\\ \\ Digital Twins](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/04-bridging-the-gap-real-world-data-integration/02-digital-twins.html 'next page') [View this page as Markdown](https://docs.nvidia.com/learning/physical-ai/getting-started-with-isaac-lab/latest/transfer-policies-from-simulation-to-reality/04-bridging-the-gap-real-world-data-integration/01-actuator-modeling.html.md 'View this page as clean Markdown for LLMs and AI agents') [NVIDIA](https://www.nvidia.com) [Privacy Policy](https://www.nvidia.com/en-us/about-nvidia/privacy-policy.md/) | [Manage My Privacy](https://www.nvidia.com/en-us/about-nvidia/privacy-center.md/) | [Do Not Sell or Share My Data](https://www.nvidia.com/en-us/preferences/start.md/) | [Terms of Service](https://www.nvidia.com/en-us/about-nvidia/terms-of-service.md/) | [Accessibility](https://www.nvidia.com/en-us/about-nvidia/accessibility.md/) | [Corporate Policies](https://www.nvidia.com/en-us/about-nvidia/company-policies.md/) | [Product Security](https://www.nvidia.com/en-us/product-security.md/) | [Contact](https://www.nvidia.com/en-us/contact/) Copyright © 2025 NVIDIA CORPORATION & AFFILIATES. 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