Operating in emergency or conflict areas is complicated. Difficult-to-access or rugged terrain, isolated or heavily damaged areas, unexpected situations, changing or very difficult weather conditions. The use of autonomous systems is very convenient to deal with these critical situations, but obtaining data to train these systems is incredibly complicated for obvious reasons, the real risk of taking data in situ.
Synthetic data allows new-generation-sensor and AI-based autonomous systems to be safely trained, recreate any uncommon situation (however implausible it may be), simulate any weather condition, and simulate any vehicle, ship, or robot. Anyverse makes it possible and improves the training and performance of autonomous systems for this use case while reducing development costs by allowing the simulation of any scene impossible to find in the real world.
Generate complex training scenarios impossible to recreate in the real world, add multiple criteria (any terrain, any region, any object…), reproduce any emergency vehicle (drone, truck, UAV, …), customize camera locations, and reach different angles (air or land) and simultaneous cameras, allowing your AI to:
Hyperspectral accuracy to simulate any terrain.
Simulate the specific sensors your system is using in the real world (cameras, LiDAR, and more).
In scenarios and 3D assets
variability to avoid bias in your system.
In data generation.
Perfect annotations, depth, segmentation, and more.
The platform counts with a comprehensive assets library to build thousands of different customizable defense & security-oriented scenes, including: people, outdoors assets (forest, rural, desert, and more), variety of obstacles, hostile and friendly objects, variety of building with different levels of damage, variety of vehicles (land and air), and more.
and discover the agile, and cost-efficient way to develop your autonomous systems
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