LiDAR
Light Detection and Ranging; a remote sensing technology that uses laser pulses to measure the distance and three-dimensional shape of targets. It is widely applied in fields including archaeology, surveying and mapping, and autonomous driving.
Timeline (last 90 days)
Apple has historically preferred to carry new technology in mature product categories, for example first validating high-refresh-rate displays and LiDAR on the iPad and then gradually cascading them down.
The noise problem of sparse LiDAR input has long been a pain point for the practical deployment of neural implicit mapping.
Neural implicit SDF geometry recovered from sparse and noisy LiDAR input is prone to high-frequency jitter and surface artifacts.
In the field of autonomous driving, LiDAR data collection is costly and difficult to annotate, and generating high-quality LiDAR point clouds from multi-view images can lower the barrier to data acquisition.
Web pages can usually only access the camera feed, whereas native apps can call on LiDAR, IMU, gyroscope and the like for precise spatial tracking.
The heavier the snowfall, the more point cloud points land on the surfaces of objects such as vehicles, providing the detector with richer geometric information.
Evaluation based on the WADS-3D and CADC datasets found that object detection accuracy continuously improves as snowfall intensity increases.
Snowfall as noise has a negative impact on LiDAR detection, but this negative effect is offset by a significant increase in the number of object point clouds.
It is an industry consensus that LiDAR is a core sensor in autonomous driving perception systems and that its performance degrades significantly in adverse weather.
Once covered with snow, the surface becomes diffusely reflective, laser energy scatters in all directions, and the receiver can capture more valid return signals.
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All Facts (20)
iPhone 12 Pro and later models are equipped with a LiDAR scanner, which can quickly generate a 3D mesh of a room.
60%UnverifiedApple Vision Pro is equipped with a LiDAR depth sensor, a high-resolution Micro-OLED display, and an M2 chip.
60%UnverifiedA point cloud is a collection of three-dimensional spatial coordinates collected by LiDAR or depth cameras.
60%UnverifiedApple has historically preferred to carry new technology in mature product categories, for example first validating high-refresh-rate displays and LiDAR on the iPad and then gradually cascading them down.
50%UnverifiedNeural implicit SDF geometry recovered from sparse and noisy LiDAR input is prone to high-frequency jitter and surface artifacts.
50%UnverifiedThe noise problem of sparse LiDAR input has long been a pain point for the practical deployment of neural implicit mapping.
50%UnverifiedIn the field of autonomous driving, LiDAR data collection is costly and difficult to annotate, and generating high-quality LiDAR point clouds from multi-view images can lower the barrier to data acquisition.
50%UnverifiedWeb pages can usually only access the camera feed, whereas native apps can call on LiDAR, IMU, gyroscope and the like for precise spatial tracking.
50%UnverifiedEvaluation based on the WADS-3D and CADC datasets found that object detection accuracy continuously improves as snowfall intensity increases.
50%UnverifiedIt is an industry consensus that LiDAR is a core sensor in autonomous driving perception systems and that its performance degrades significantly in adverse weather.
50%UnverifiedOnce covered with snow, the surface becomes diffusely reflective, laser energy scatters in all directions, and the receiver can capture more valid return signals.
50%UnverifiedVehicle surfaces in dry conditions exhibit strong specular reflection properties, and laser beams may be reflected in non-receiving directions, resulting in missing point clouds.
50%UnverifiedEvaluating perception systems using only coarse-grained binning by weather severity without considering object-level data leads to misleading conclusions about detector robustness.
50%UnverifiedThe heavier the snowfall, the more point cloud points land on the surfaces of objects such as vehicles, providing the detector with richer geometric information.
50%UnverifiedSnowfall as noise has a negative impact on LiDAR detection, but this negative effect is offset by a significant increase in the number of object point clouds.
50%UnverifiedCopernicus DEM has a resolution of approximately 10 meters, and LiDAR-collected data can reach sub-meter level.
50%UnverifiedThe X50 Ultra is equipped with a suspension system that can dynamically adjust its height, combined with LiDAR and structured light sensors to achieve cross-step capability.
50%UnverifiedWaymo's sensor suite consists of a multimodal fusion system combining LiDAR, cameras, and radar.
50%UnverifiedThe perception layer relies on fused inputs from LiDAR, cameras, and millimeter-wave radar, with object recognition performed by deep convolutional neural networks.
50%UnverifiedPure photogrammetry solutions have the lowest cost but take longer, while mobile devices equipped with LiDAR have an advantage in speed and convenience but slightly inferior absolute accuracy compared to professional laser scanning
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