Explore the world of robotic perception through a comprehensive video series that delves into designing advanced systems using MATLAB® and Simulink®. Gain insights from MathWorks experts on computer vision, deep learning, and signal processing techniques crucial for enabling robots and unmanned vehicles to interpret their surroundings. Learn practical skills such as labeling ground truth for object detection, training and validating object detectors, implementing sensor fusion for orientation estimation, and designing digital filters. Discover how to preprocess data for deep learning, design and train YOLOv2 networks, import pretrained networks, and deploy YOLOv2 to an NVIDIA Jetson. Benefit from real-world examples featuring successful student teams who have applied MATLAB and Simulink in their robotic perception projects.
Overview
Syllabus
Labeling Ground Truth for Object Detection.
Training and Validating Object Detectors.
Sensor Fusion for Orientation Estimation.
Designing Digital Filters with MATLAB.
Estimating Direction of Arrival with MATLAB.
Data Preprocessing for Deep Learning.
Design and Train a YOLOv2 Network in MATLAB.
Import Pretrained Deep Learning Networks into MATLAB.
Deploy YOLOv2 to an NVIDIA Jetson.
Taught by
MATLAB
