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Fundamentals of Perception in Autonomous Driving

Course: Fundamentals of Self-Driving Cars: From Basics to Advanced Autonomy

Introduction to Sensors in Perception

In autonomous driving, perception is the process by which a self-driving car understands its environment. Sensors are the "eyes and ears" of the vehicle, capturing data to detect objects, lanes, pedestrians, and more. The core sensor types include cameras, LiDAR, and RADAR, each with unique principles that complement one another for robust perception.

Why multiple sensors? A single type can't handle all conditions—like low light or bad weather—due to limitations in range, resolution, or environmental robustness.

Key principles overview: - Cameras: Mimic human vision using light. - LiDAR: Uses laser pulses for precise 3D mapping. - RADAR: Employs radio waves for velocity and distance detection.

This multi-sensor fusion ensures safety and reliability in the perception pipeline, building on core components like the vehicle's compute and actuation systems from prerequisites.

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