Real-Time LiDAR Processing
Real-Time LiDAR Processing refers to the immediate analysis of 3D point cloud data generated by a LiDAR sensor as it is being collected. Instead of storing raw data for post-processing, onboard or edge computing systems use specialized algorithms to instantly interpret the scene—identifying objects (vehicles, pedestrians, obstacles), extracting features (lane markings, curbs), and making decisions (for autonomous vehicle navigation, robot path planning, or security perimeter monitoring). This capability is critical for applications requiring instantaneous reaction, such as self-driving cars, real-time mapping, and dynamic obstacle avoidance for drones and robots.
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Onboard or edge computing that processes LiDAR point clouds with near-zero latency.
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Enables immediate object detection, classification, and tracking in a 3D space.
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Critical for autonomous vehicle perception, robotic navigation, and augmented reality.
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Reduces data bandwidth requirements by sending only processed information, not raw point clouds.
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Uses algorithms like clustering, segmentation, and neural networks for scene understanding.
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The key to unlocking responsive, intelligent behavior in mobile autonomous systems.
See and understand the 3D world instantly. Real-Time LiDAR Processing enables immediate perception and decision-making for autonomous systems.
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