This article is part of the Autoware series. Check out the full series: Part 1, Part 2

In this article, we will learn how to build an AutoWare.auto package and create a YonoArc block from this package. But first what is Autoware.auto and how it’s different from Autoware.ai

Autoware.Auto is a project supported by the Autoware Foundation. It is a clean slate rewrite of Autoware. Autoware.auto applies best-in-class software engineering practices, including pulling request reviews, pull request builds, comprehensive documentation, 100% code coverage, a coding style guide, and a defined development and release process, all managed by an open-source community…

This article is part of a series. Check out the full series: Part 1

Welcome to the second part of our Deep learning for Embedded Linux Series. TFLite models are very suitable for many different hardware types, including mobile phones, embedded Linux devices, and microcontrollers due to low latency and small binary size.

In this Pipeline, I’m running the COCO SSD MobileNet v1 TFLite model on a Raspberry pi 4. The input for the model also comes from the camera, which is connected to the Raspberry pi.

The cool thing about this, besides the exceptional performance of the TFLite model…

Three years ago, Microsoft released one of its first open-source projects. AirSim, drones, and ground vehicles simulator to accelerate autonomous vehicle research. Since then, AirSim’s popularity overgrew with many opensource projects in AI, deep learning, computer vision, and reinforcement learning. The simulator can be used as a simulation environment with different available Binariess each simulates a diverse, visually realistic environment. It can also be used as a hardware-in-loop with popular flight controllers such as PX4.

AirSim supports many sensors like Cameras, Lidars, GPS, IMU, Magnetometer, Barometer, and Distance sensor. And as you can see from the video above, you…

One great feature of YonoArc is the ability to create a block from any ROS package. So you can reuse all of your ROS nodes, and extend your toolbox with ready ROS packages from the great ROS community.

In this tutorial, you will be able to develop a ROS2-based YonoArc block that is written in Python. This block takes an image as input, performs semantic segmentation on it, then publish the image masked with the segmentation classes as an output. we will use a ready ROS2 package from this Github repo.

Building the block’s environment.

1. Open YonoEBuilder from Yonohub main view.
2. At the top…

In the previous article, we’ve seen how to encapsulate CarMaker inside a YonoArc’s block and publish some of the user-accessible quantities on the dashboard. This would be very useful in test data collection, where we can run many parallel test runs, save the big data generated on YonoDrive and share it across our team.

But we can do even more with CarMaker inside YonoArc’s Pipelines. We can close the loop and add some input ports to the block. This would open up a whole new world where we can integrate CarMaker easily with our arsenal of blocks. YonoArc blocks can…

If you’re here you probably heard about CarMaker or even used it before. But if it’s your first time get ready to be introduced to one of the most complete simulation solutions in the automotive. It offers the ability to develop and test systems and system networks in their entirety within the whole vehicle in realistic scenarios.

We have developed the simulation solution CarMaker specifically for testing passenger cars and light-duty vehicles. Using our software, you can accurately model real-world test scenarios, including the entire surrounding environment, in the virtual world. Our powerful and real-time capable models for vehicles, roads…

Deep Learning is another type of machine learning algorithms that is based on artificial neural networks. It’s has been around since the 1980s but in the recent decade, it has achieved impressive results in different fields.
Deep Learning models were able to achieve higher accuracy than the other Machine learning approaches. But this comes at the price, as it requires large amounts of training data and computation power.

Why Deep Learning at the edge?

That’s why its hard to deploy every deep learning model on resources limited hardware like embedded systems and mobile devices. Many applications use cloud infrastructure for deep learning inference but this is…

For the past weeks, I had the opportunity to try one of the most promising innovative products in the automotive industry and I would like to share my experience and a quick demo with you.

Welcome to Yonohub!

“ Yonohub is a web-based cloud system for building, sharing and evaluating complex autonomous vehicle systems that consist of many building blocks. Yonohub features a drag-and-drop tool to build complex systems, a marketplace to share and monetize blocks, a builder for custom development environments, and much more.”

Yonohub offers several powerful and easy-to-use apps to support developers and researchers…