AEye Library
AEye’s most recent white papers, profiles, articles, videos, resources, and blog posts…
Rethinking the Three “Rs” of LiDAR: Rate, Resolution and Range
Conventional metrics used for evaluating the performance of LiDAR for autonomous vehicles (such as frame rate, full frame resolution, and detection range) do not sufficiently address the challenges facing autonomous driving. In response, AEye proposes three new metrics for extending LiDAR evaluation, including: extending the metric of frame rate to include object revisit rate; expanding resolution to capture instantaneous resolution; and extending detection range to reflect the more critically important object classification range.
The Future of Autonomous Vehicles: Part I – Think Like a Robot, Perceive Like a Human
The artificial intelligence that drives autonomous vehicles will require artificial perception that is modeled after the greatest perception engine on the planet — the human visual cortex.
AEye iDAR: Sensor Performance Validation Report (VSI Labs)
Based off of their findings, VSI Labs determined that AEye's iDAR system "can detect and potentially classify objects with enough precision, accuracy, and distance not possible with conventional LiDAR or camera sensors."
The Future of Autonomous Vehicles: Part II – Blind Technology without Compassion Is Ruthless
To make truly safe, autonomous vehicles, will we need to “teach” them empathy and compassion?
Elon Musk Is Right: LiDAR Is a Crutch (Sort of.)
Mr. Musk is right. Relying solely on LiDAR can steer autonomous vehicle companies into innovation cul-de-sacs.
AEye Team Profile: Umar Piracha
LiDAR is enabling self-driving cars to become a reality by ensuring that they drive with the least amount of risk to other drivers or those around it. LiDAR is necessary for autonomous vehicles because it reduces the burden of real-time perception and prediction, which is not possible using AI and stereo-cameras alone.
AEye Team Profile: Ove Salomonsson
LiDAR is the final sensor modality that is needed to make ADAS systems (and eventually full autonomy) work effectively in all conditions. LiDAR is more deterministic by nature, as it can detect and measure the distance to all objects. And with an agile LiDAR, such as AEye’s iDAR, this can be done incredibly fast with the added ability to classify objects and determine their velocity.
AEye Team Profile: Amy Ishiguro
An NPI Engineer is responsible for bringing a product from the engineering sample phase to mass production. At the end of the day, my goal is to deliver a safe, reliable, and cost-efficient product at volume.
iDAR Sees Only What Matters
Only iDAR brings intelligence to the sensor layer. By fusing 1550 nanometer, solid-state agile LiDAR with a low-light HD camera, CV algorithms, and embedded AI - at the sensor - iDAR filters out the most important aspects of a given scene. With iDAR, the vehicle’s perception system can target only the salient 5% of data it needs to safely navigate. Watch how.
This Is AEye
AEye values integrity, innovation, and a dedication to change the world by bringing sensible, problem-solving ADAS and Mobility perception solutions to market. Will you join us in building a safer future?
AEye Sets New Benchmark for LiDAR Range
Introducing 1KM AEye has set a new benchmark for LiDAR range. In performance specification tests monitored and validated by VSI Labs, AEye’s iDAR system acquired and tracked a truck at 1,000 meters – or one kilometer – five times the distance current LiDAR systems are able to detect! Watch now...