Developing ADAS and Automated Driving systems for urban environments is a high-stakes challenge. Intersections are particularly difficult to validate because autonomous vehicles must navigate complex… 更多内容 >>

Guest BloggerGeorge Amarantidis Koronaios is a Developer Advocate at MathWorks. He focuses on technical engagement with the engineering community, with an emphasis on Design Automation workflows and… 更多内容 >>

The previous post introduced a MATLAB-based traffic swarm framework capable of generating randomized ambient traffic with configurable safety and behavioral parameters. Realistic traffic scenarios… 更多内容 >>

NVIDIA has recently introduced a Synthetic Data Generation (SDG) workflow for traffic scenarios, enabling the creation of photorealistic synthetic traffic videos using Cosmos models, such as Cosmos… 更多内容 >>

The next wave of innovation isn’t happening on roads or highways — it’s unfolding in fields, mines, and construction sites. Tractors, excavators, and haul trucks are becoming increasingly… 更多内容 >>

Generative AI for Robotics with MATLAB and… 更多内容 >>

Autonomous systems have emerged as transformative technologies across industries, from Unmanned Aerial Vehicles (UAVs) to maritime robotics. Central to their functionality is the autopilot — a… 更多内容 >>

Explore the essentials of SLAM and its role in robotics and autonomous systems. This blog post by our expert Jose Avendano Arbelaez provides a quick overview of SLAM technologies and its… 更多内容 >>

I recently worked with Eric Hillsberg, Product Marketing Engineer, to assess MathWorks’ tools for inertial navigation, supported from Navigation Toolbox and Sensor Fusion and Tracking Toolbox. In… 更多内容 >>

Recently, George Chowdhury, an industry analyst of robotics from ABI Research, interviewed me on the significance of robotics simulation, particularly using MATLAB and Simulink, for his report on… 更多内容 >>