Engineering and Technology
Learn to fuse lidar point clouds, radar signatures, and camera images using Kalman Filters to detect and track vehicles and pedestrians over time.
The Sensor Fusion Engineer course on Udacity covers a range of topics related to sensor fusion. Students will learn how to process raw lidar data by applying filtering, segmentation, and clustering techniques to detect other vehicles on the road. They will also explore lidar obstacle detection and how to fuse camera images with lidar point cloud data. This involves extracting object features, classifying objects, and projecting camera images into three dimensions for fusion with lidar data. Additionally, students will analyze radar signatures to detect and track objects, calculating velocity and orientation while accounting for distortions, noise, and occlusions. The course also covers the use of Kalman filters to fuse data from multiple sources, including building extended and unscented Kalman filters for tracking nonlinear movement.
by Udacity
Learn to fuse lidar point clouds, radar signatures, and camera images using Kalman Filters to detect...
by Udacity
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by Udacity
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by Udacity
Learn how to locate an object in a moving system and track it over time.
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This course provides an introduction to cyber-physical systems with an industrial perspective.
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Master the deep reinforcement learning skills that are powering amazing advances in AI—and start app...
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by Udacity
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