Cognata’s AV off-road simulation is designed to test, train and validate perception and control challenges for terrains that do not offer a clear road definition. This simulation platform uses synthetic data with a digital twin environment, and delivers a new level of realism in training and validating Next Generation Combat Vehicles, Manned Fighting Vehicles & Robotic Controlled Vehicles for defense-specific applications.
Cognata is working with the Israeli Ministry of defense.
Autonomous military vehicles are mainly deployed in difficult terrains, areas with changing weather, and war zones. The use of autonomous vehicles in such environments eliminates the chances of harm to army personnel.
Using autonomous vehicles and robots reduces human casualties and enhances performance, however, autonomy is not an easy task. To attain autonomous behavior, vehicles should recognize vehicles and bystanders, define passable paths, avoid obstacles along the route, and predict moving objects.
For the scenarios catalog, we have created a variety of different scenes designed to train and validate off-road driving from identifying a drivable path to overcoming obstacles and difficult road conditions.
We have also created a rich catalog with off-road special synthetic assets such as people, obstacles, and special defense-related hostile and friendly elements.
