Learn how to design perception systems for robots and unmanned vehicles using MATLAB and Simulink. Gain knowledge in computer vision, deep learning, and signal processing to help robots understand their surroundings. The course covers topics such as labeling ground truth, object detection, sensor fusion, digital filter design, deep learning data preprocessing, and deploying networks to hardware. The intended audience for this course includes robotics enthusiasts, engineers, and students interested in perception systems for autonomous machines.
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
