AEye Introduces iDAR System for Autonomous Vehicles


AEye, a startup with significant investors, has announced the AE100, it’s first robotic perception system for autonomous vehicles. The AE100 is a solid state system based on the company’s Intelligent Detection and Ranging (iDAR) technology. iDAR is made of up three components working in synergy.

Agile 1550mm Micro-optical Mechanical (MOEMS) laser-light range detection (LiDar), distributed artificial intelligence, and software-definable hardware. AEye says that the combination allows the iDAR unit to adapt dynamically to the real-time demands of semi-automated and fully autonomous vehicles.

Designed to analyse the entire 360-degree view around the car, versus fixed pattern LiDar more often found on today’s semi-autonomous vehicles, the AEye iDAR AE100 system features embedded intelligence capable of:

  • Coverage: The AE100 can use dynamic patterns for mapping the environment, as it is not tied to one fixed mode. In evaluating any given scene, AE100’s software definable scanning delivers more than 10x the 3D resolution over legacy systems.
  • Speed: The AE100 is three times faster than current LiDAR systems, and does not miss any objects between scans while identifying and solving any temporal anomalies. This reduces scan gaps, resulting in more than 25 feet of faster response distance at average highway speeds—more than two car lengths.
  • Range: The AE100 extends effective range at comparable resolution by 7-10x over currently deployed LiDAR systems.

AEye’s iDAR technology mimics how a human’s visual cortex focuses on and evaluates potential driving hazards. Using a distributed architecture, iDAR critically and dynamically assesses general surroundings, while applying differentiated focus to track targets and objects of interest, while always critically assessing general surroundings. That enables accessible direct detection for every pixel and voxel in each frame.

AEye says that this scalable, software-definable approach enables iDAR to deliver higher accuracy, longer range, and more intelligent information to optimize path planning software, thereby enabling improved autonomous vehicle safety and performance at a reduced cost.