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Accelerating Autonomous Engineering
Digital Twin Based Perception, Validation and Safety for AV, ADAS and Smart Cities
Industries
Autonomous Vehicles
ADAS
Defense
Agriculture
Construction & Mining
Warehouse
Smart Cities
But don't just take our word..
Features
Sensors
RGB HD cameras
Fisheye camera - Omnidirectional model 250°
Radar – support in mmWave models
LiDAR support + Rolling Shutter
LWIR – Thermal camera
Ultrasonic camera
Simple integrations
Model Interfaces: Simulink, ROS
Tool Interfaces: SUMO
Automated testing with Jenkins and Bamboo
Supported standards: OpenDrive, OpenScenario
Analytics Platform
Ready-to-use pass/fail criteria for validation and certification of AV and ADAS
Powerful custom rule authoring
Trend mining for large scale simulation
AV virtual certification of regulatory requirements
Digital Twin
Library of pre-built scenarios for common automated driving functions
Different terrain types and vehicle physics behavior
Comprehensive assets catalog – vehicles, pedestrians, cyclists, vegetation, buildings, and more.
Vehicle Physics
More than 1,000 unique parameters adjusting to the specific vehicle models and dynamics
Customized 3D asset import as dynamic/moving objects or Ego cars
Ego vehicles hight ranging from 1.5m to 4m, including custom tire diameter and tracks
DNN Photorealism
Photorealism synthetic data enabled by deep neural networks (DNN)
Pixel perfect, Accurate, ground truth consistent annotation in every frame
AI with geo-specific interactive behavior profiles
Sensors
RGB HD cameras
Fisheye camera - Omnidirectional model 250°
Radar – support in mmWave models
LiDAR support + Rolling Shutter
LWIR – Thermal camera
Ultrasonic camera
Simple integrations
Model Interfaces: Simulink, ROS
Tool Interfaces: SUMO
Automated testing with Jenkins and Bamboo
Supported standards: OpenDrive, OpenScenario
Analytics Platform
Ready-to-use pass/fail criteria for validation and certification of AV and ADAS
Powerful custom rule authoring
Trend mining for large scale simulation
AV virtual certification of regulatory requirements
Digital Twin
Library of pre-built scenarios for common automated driving functions
Different terrain types and vehicle physics behavior
Comprehensive assets catalog – vehicles, pedestrians, cyclists, vegetation, buildings, and more.
Vehicle Physics
More than 1,000 unique parameters adjusting to the specific vehicle models and dynamics
Customized 3D asset import as dynamic/moving objects or Ego cars
Ego vehicles hight ranging from 1.5m to 4m, including custom tire diameter and tracks
DNN Photorealism
Photorealism synthetic data enabled by deep neural networks (DNN)
Pixel perfect, Accurate, ground truth consistent annotation in every frame
AI with geo-specific interactive behavior profiles
News
April 2023
As the world moves towards a future of autonomous vehicles (AVs), it becomes increasingly important to ensure that these vehicles are…
January 2023
Key Highlights Cognata launches a new product service using Microsoft Azure that allows Automotive Customers to virtually evaluate ADAS/AV sensors through…
November 2022
Joint offering to provide a comprehensive solution for testing perception and planning Tel Aviv, Israel, November 21, 2022 – Foretellix…
November 2022
Rehovot, Israel, Nov. 17, 2022 – Cognata today announced that it has been named a CES® 2023 Innovation Awards Honoree for…
October 2022
Rehovot, Israel, Oct 19, 2022 – Cognata Ltd announces today the launch of a new collaboration with Xylon, to provide a…
October 2022
We are excited to announce that Cognata won the EIT Urban Mobility‘s RAPTOR Pedestrian Road Safety Pilot in Tel Aviv, Israel!…
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