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Training / Education

LIDAR for ADAS and Autonomous Sensing
2024-04-19
Advanced Driver Assist System (ADAS) and autonomous vehicle technologies have disrupted the traditional automotive industry with potential to increase safety and optimize the cost of car ownership. Light detection and ranging (LIDAR) sensing, a sensing method that detects objects and maps their distances, is seeing rapid growth and adoption in the industry. However, the sensor requirements and system architecture options continue to evolve. This course will provide the foundation on which to build LIDAR technologies in automotive applications.
Training / Education

Infrared Camera for ADAS and Autonomous Sensing
2024-04-18
Advanced Driver Assist System (ADAS) and autonomous vehicle technologies have disrupted the traditional automotive industry with potential to increase safety and optimize the cost of car ownership. Among the challenges are those of sensing the environment in and around the vehicle. Infrared camera sensing is seeing a rapid growth and adoption in the industry. The applications and illumination architecture options continue to evolve. This course will provide the foundation on which to build near infrared camera technologies for automotive applications.
Training / Education

ADAS Application Automatic Emergency Braking
2024-04-15
Active Safety, Advanced Driver Assistance Systems (ADAS) are now being introduced to the marketplace as they serve as key enablers for anticipated autonomous driving systems. Automatic Emergency Braking (AEB) is one ADAS application which is either in the marketplace presently or under development as nearly all automakers have pledged to offer this technology by the year 2022. This one-day course is designed to provide an overview of the typical ADAS AEB system from multiple perspectives.
Training / Education

Exploration of Machine Learning and Neural Networks for ADAS and L4 Vehicle Perception
2024-03-27
Convolutional neural networks are the de facto method of processing camera, radar, and lidar data for use in perception in ADAS and L4 vehicles, yet their operation is a black box to many engineers. Unlike traditional rules-based approaches to coding intelligent systems, networks are trained and the internal structure created during the training process is too complex to be understood by humans, yet in operation networks are able to classify objects of interest at error rates better than rates achieved by humans viewing the same input data.
Training / Education

Robotics for Autonomous Vehicle Systems Bootcamp
2024-02-02
The Robotics for AV Systems Bootcamp was developed by SAE International and Clemson University, with industry guidance from Argo AI. This rigorous, twelve-week, virtual-only experience is conducted by leading experts in industry and academia. You’ll develop a deep, technical understanding of how to build autonomous systems by learning to program a mobile robot through hands-on approaches using ROS 2, Gazebo, and Python.
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