MathWorks
Canvas Category Software : Information Technology : Data & AI
MathWorks is the leading developer of mathematical computing software for engineers and scientists.
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Foretellix and MathWorks Partner on Innovative Toolchain to Accelerate Mazda’s Next Generation AV Development
Foretellix and MathWorks have partnered to accelerate Mazda’s next-generation autonomous vehicle (AV) development. The integration of Foretellix’s Foretify platform with MathWorks’ Simulink and Automated Driving Toolbox enables developers to test and scale scenarios in a virtual environment, reducing time to market while improving system quality and safety. By moving real-world driving data into the virtual simulation environment, engineering teams can identify edge cases, uncover gaps in coverage, and validate performance earlier in the development process, resulting in safer and more robust autonomous systems.
Implementing a Workflow for Deploying and Integrating Deep Learning Networks on PLCs for Industrial Automation
Our team at Beckhoff Automation has implemented a new workflow that combines MATLAB® tools and Beckhoff Automation products to enable low-code design and AI model training—and simplifies the deployment and integration of those models on industrial targets. Working with MathWorks engineers, we developed this workflow and demonstrated it on an example quality control application that involved the visual inspection of hex nuts. While this simple application classifies hex nuts as either defective or not, demonstrating a straightforward use case, the steps in the workflow can be applied to accelerate the development and deployment of much more sophisticated and complex applications.
After collecting and preparing the data to be used in a deep learning application, the workflow’s first step is training a deep learning model. With MATLAB and Deep Learning Toolbox, there are several ways to do this, including training a network from scratch with Deep Network Designer app, defining a deep learning model as a function and using a custom training loop, or retraining a pretrained model with new data, also known as transfer learning. If there is a small amount of abnormal data, anomaly detection methods such as FCDD and PatchCore, which are included in the Automated Visual Inspection Library for Computer Vision Toolbox™, are also effective.
Universal Robots Expands Partnership with MathWorks by Joining Connections Program
Universal Robots, the Danish collaborative robot (cobot) company, has further strengthened its partnership with MathWorks, the leading developer of mathematical computing software, by joining the Mathworks Connections Program. The program supports organizations that develop and distribute complementary, commercially available products, training, and consulting based on MATLAB® and Simulink®. Last year, MathWorks became a UR+ partner within the Universal Robots ecosystem, consisting of more than 300+ approved developer companies creating products for the UR platform.
NVIDIA Supercharges Autonomous System Development with Omniverse Cloud APIs
With Omniverse Cloud APIs, developers can enhance the workflows they’re already using with high-fidelity sensor simulation to tackle the challenge of developing full-stack autonomy. This not only streamlines the development process but also lowers the barriers to entry for companies of virtually all sizes developing autonomous machines.
Developers and software vendors such as CARLA, MathWorks, MITRE, Foretellix and Voxel51 underscore the broad appeal of these APIs in autonomous vehicles. CARLA is an open-source AV simulator used by more than 100,000 developers. With Omniverse Cloud APIs, CARLA users can enhance their existing workflows with high-fidelity sensor simulation. Similarly, MITRE, a nonprofit that operates federally funded R&D centers and is dedicated to improving safety in technology, is building a Digital Proving Ground for the AV industry to validate self-driving solutions. The DPG will use the Omniverse APIs to enable core sensor simulation capabilities for their developers. MathWorks and Foretellix provide critical simulation tools for authoring, executing, monitoring, and debugging of testing scenarios. As the GTC 2024 demo showed, combining such simulation and test automation tools with the APIs forms a powerful test environment for AV development. And, by integrating the APIs with Voxel51’s FiftyOne platform, developers can easily visualize and organize ground-truth data generated in simulation for streamlined training and testing.
Leading industrial-sensor solution provider SICK AG is working on integrating these APIs in its sensor development process to reduce the number of physical prototypes, iterate quickly on design modifications and validate the eventual performance. These validated sensor models can eventually be used by autonomous systems developers in their applications.
Developers will also have access to sensor models from a variety of manufacturers, including lidar makers Hesai, Innoviz Technologies, Luminar, MicroVision, Robosense, and Seyond, visual sensor suppliers OMNIVISION, onsemi, and Sony Semiconductor Solutions, and Continental, FORVIA HELLA, and Arbe for radar.
Developing AI Predictive Maintenance Models
How to integrate AI into engineering
Most of the focus on AI is all about the AI model, which drives engineers to quickly dive into the modelling aspect of AI. After a few starter projects, engineers learn that AI is not just modelling, but rather a complete set of steps that includes data preparation, modelling, simulation and test, and deployment