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Our flight control technology leverages advanced reinforcement learning (RL) to propel the future of Advanced Air Mobility (AAM). By integrating RL, we enable autonomous control in electric vertical takeoff and landing (eVTOL) vehicles, agriculture aerial sprayers and cargo drones, optimizing their performance for safety, efficiency, and ecological sustainability. RL algorithms like Q-learning, policy gradient, and actor-critic methods allow these vehicles to learn optimal flight policies through interaction with their environment, adjusting control signals in real-time to achieve objectives such as obstacle avoidance, trajectory optimization, and fuel efficiency. We also employ differentiable simulators for enhanced training efficiency, ensuring that our systems can learn from simulated data before being deployed in real-world scenarios. Safety is paramount, with strategies like safe exploration and sim-to-real transfer ensuring that learning occurs without compromising the integrity of the flight. This technology is set to revolutionize urban and regional air travel, making it autonomous, safer, and more accessible.

Website http://www.aviusaero.com
Employees View employees
Founded 2024
Industry Aviation & Aerospace

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