AI Flight Controllers for Improved Flight Characteristics and Fault Tolerance

人工智能系统在使飞行控制系统更安全、更稳健和更具成本效益方面发挥着重要作用。路飞人工智能开发了自适应神经网络，允许实时机载学习和适应。在这个项目中，我们将通过模拟和飞行测试开发和演示一个人工智能飞行控制器，可以适应无人机飞行器及其环境的变化。此外，该项目还将为航空领域基于人工智能的自主监管制定一个安全案例框架。这项工作由约克大学安全自主研究所领导，将支持英国在这一领域更广泛的监管目标，并将英国定位为商业用途自动驾驶系统安全部署的领导者。总的来说，这种新功能将展示人工智能控制器如何为城市空中交通（UAM）和大型民用应用提供替代的、具有成本效益的解决方案，并改善监管机构眼中的安全案例。

AI systems have a role to play in making flight control systems safer, more robust and cost-effective. Luffy AI has developed adaptive neural networks that allow real-time onboard learning and adaption. In this project, we will develop and demonstrate through simulation and flight testing an AI flight controller that can adapt to variations in both a drone flight vehicle and its environment. In addition, the project will develop a framework for the safety case for the regulation of AI based autonomy in aviation. This work led by the Institute for Safe Autonomy, at the University of York, will support the UK's wider regulatory ambitions in this area and position the UK as a leader in the safe deployment of autonomous systems for commercial use.Overall, this new capability will demonstrate how AI controllers can provide an alternative, cost-effective solutions for Urban Air Mobility (UAM) and large civil applications and improve their safety case in the eyes of regulators.