This graduate-level sequence explores the mathematical and algorithmic foundations of robotic perception. Students progress from modeling sensor noise to implementing advanced state estimation (Kalman Filters) and computer vision techniques, culminating in deep-learning-based object detection for real-time autonomous systems.

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