Hexagon | AutonomouStuff FLIR ADK

Description

The FLIR ADK is a cost-effective way to develop the next generation of automotive thermal vision for advanced driver assistance systems (ADAS) and autonomous vehicles (AV). Thermal infrared cameras are the best sensor technology for pedestrian detection, reliably classifying people in cluttered environments and giving analytics the critical information needed for automated decision-making. The ADK’s rugged, IP67 rated enclosure incorporates a heated window for all-weather driving. With the GMSL and USB interfaces, installation is plug-and-play easy.

Thermal camera advantages include:

• object detection in complete darkness at long distances.
• clear views through conditions that obscure regular cameras, such as smoke, rain, snow, dust and light fog.
• improved object detection in landscapes with analogous colors or patterns that trick regular cameras, creating potentially dangerous scenarios where objects of interest are not recognized.

AutonomouStuff is now offering Artificial Intelligence (AI) solutions for the FLIR ADK as a part of our software suite. We are training models for autonomous applications and working closely with Hexagon AI groups to stay up to date on the latest in AI advancements throughout the industry.

Features

• 640 × 512 resolution with 24°, 32°, 50°, and 75° horizontal field-of-view options
• Operate in all-weather conditions with heated external window
• See clearly in day, night and through fog, smoke, sun and headlight glare
• Detect and classify pedestrians even in cluttered environments
• Add to ADAS and AV driving systems to complement existing sensors
• Quickly mount the heated IP67-rated kit and drive in all-weather conditions
• USB 2.0, GMSL, Ethernet, and FPD-Link interfaces
• Detection and classification range of up to 200 meters (adult pedestrian)
• Provides selectable 60 Hz/30 Hz thermal video to host computer systems
• Selectable 16-bit raw or 8-bit compressed data formats
• Compatible with NVIDIA®, Linux®, Windows®, ROS, and ADTF