In the May 2019 issue of SAE’s Autonomous Vehicle Engineering (AVE) magazine, AEye’s technical product manager, Indu Vijayan, argues that conventional metrics used for evaluating the unique capabilities of more advanced lidar systems are inadequate, failing to address real-world driving problems facing autonomous vehicles. In ‘New Performance Metrics for Lidar,’ Indu proposes that new measurements, such as object revisit rate and instantaneous (angular) resolution, are more advantageous for autonomous vehicle development.
Lidar Leader Award 2019 Winner – Outstanding Innovation in Lidar On January 29th, 2019, AEye was awarded "Outstanding Innovation in Lidar" for the creation of the AE110 Artificial Perception System at the second annual Lidar Leader Awards ceremony at International LiDAR Mapping Forum (ILMF) – in cooperation with Spatial Media’s Lidar Magazine. The AE110 is built on AEye’s iDAR (Intelligent Detection and Ranging) perception system, which delivers more accurate and more intelligent information faster to a self-driving car's path planning…
January 31, 2019, 6pm | Computer Vision Meetup | Sunnyvale Community Center Speaker: Abhijit Thatte, AEye VP of Software "AI for Autonomous Vehicles"
AEye takes Reuters on a drive down the Las Vegas Strip to show off how its artificial perception technology can detect up to 1000 meters and mimic human perception by focusing on important objects in a scene.
As a robotics perception pioneer bringing new, intelligent data perception to automotive vehicles, AnyAuto has named AEye among "the automotive innovations to watch closely in the year 2019."
Engineering.com: “While conventional LiDAR systems rely on an array of independent sensors that produce large quantities of data — which [then] require long processing times and extensive computing power to analyze and translate it into actionable information that a car can use” — only AEye’s iDAR system can intelligently prioritize actionable data.
Forbes details why conventional, solid-state LiDAR systems won't be enough to cultivate the future of autonomous vehicles. Instead, what will catapult autonomous vehicles into the mainstream market is faster, smarter, detection systems, like AEye's iDAR, which fuses agile LiDAR with a high-resolution, low-light camera to replicate the advanced processes of the human visual cortex.
EETimes explores AEye's use of artificial intelligence to discriminately collect data information that only matters to an AV’s path planning, instead of assigning every pixel the same priority. According to VSI's Phil Magney, "this is really edge fusion as the device is fusing the raw data with the camera data before any classification occurs.”