Uploaded October 2025 | Updated September 2026, 3 weeks ago
Whether you’re integrating an object detector into an existing application or deploying it to hardware, you have a few options when determining how to package the detector.
This step-by-step guide teaches you how to turn your model into a functional component of your project, first showing how to create a static library using MATLAB Coder™ and then taking you through the steps of creating an ROS 2 node. These deployment options allow you to integrate your model seamlessly into various applications, from standalone software to robotic systems.
Check out the other videos in the Deep Learning for 3D Object Detection series: youtube.com/playlist?list=PLn8PRpmsu08r-T6JFLhf-Bp3QcEpzE1ex
Related Resources:
- Access the materials for this video: bit.ly/3D-object-detection
- R2025b Supported and Compatible Compilers - Windows: bit.ly/4pHc49E
- MATLAB Coder Documentation: bit.ly/3Keif4B
- Prerequisites for Deep Learning with MATLAB Coder: bit.ly/3Iyjye3
- Installing Prerequisite Products: bit.ly/3KzJV3W
Chapters:
0:00 Introduction
0:29 Prerequisites for code generation
3:42 What is a static library
4:31 Code generation workflow
6:19 Set up MATLAB Coder with the coder app
8:03 Explore coder settings
12:10 Check for issues and generate a static library
14:45 Explore the generated code
18:10 ROS 2 nodes and coder configuration
20:56 Creating a ROS 2 node in MATLAB
23:16 Generate a deploy a ROS 2 node to a Jetson device
24:48 Conclusion
--------------------------------------------------------------------------------------------------------
Get a free product trial: goo.gl/ZHFb5u
Learn more about MATLAB: goo.gl/8QV7ZZ
Learn more about Simulink: goo.gl/nqnbLe
See what's new in MATLAB and Simulink: goo.gl/pgGtod
© 2025 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc.
See mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.
Whether you’re integrating an object detector into an existing application or deploying it to hardware, you have a few options when determining how to package the detector.
This step-by-step guide teaches you how to turn your model into a functional component of your project, first showing how to create a static library using MATLAB Coder™ and then taking you through the steps of creating an ROS 2 node. These deployment options allow you to integrate your model seamlessly into various applications, from standalone software to robotic systems.
Check out the other videos in the Deep Learning for 3D Object Detection series: youtube.com/playlist?list=PLn8PRpmsu08r-T6JFLhf-Bp3QcEpzE1ex
Related Resources:
- Access the materials for this video: bit.ly/3D-object-detection
- R2025b Supported and Compatible Compilers - Windows: bit.ly/4pHc49E
- MATLAB Coder Documentation: bit.ly/3Keif4B
- Prerequisites for Deep Learning with MATLAB Coder: bit.ly/3Iyjye3
- Installing Prerequisite Products: bit.ly/3KzJV3W
Chapters:
0:00 Introduction
0:29 Prerequisites for code generation
3:42 What is a static library
4:31 Code generation workflow
6:19 Set up MATLAB Coder with the coder app
8:03 Explore coder settings
12:10 Check for issues and generate a static library
14:45 Explore the generated code
18:10 ROS 2 nodes and coder configuration
20:56 Creating a ROS 2 node in MATLAB
23:16 Generate a deploy a ROS 2 node to a Jetson device
24:48 Conclusion
--------------------------------------------------------------------------------------------------------
Get a free product trial: goo.gl/ZHFb5u
Learn more about MATLAB: goo.gl/8QV7ZZ
Learn more about Simulink: goo.gl/nqnbLe
See what's new in MATLAB and Simulink: goo.gl/pgGtod
© 2025 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc.
See mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.
