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An Efficient Simulation Platform for Testing and Validating Autonomous Navigation Algorithms for Multi-rotor UAVs Based on Unreal Engine

机译:基于虚幻引擎的多转子UAV测试和验证自主导航算法的高效仿真平台

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Developing autonomous navigation algorithms without using extern positioning signals is the key to allow Multi-rotor UAVs to fly in complex environments where the GNSS signals are week or invalid. However, it is an expensive and time consuming process to develop and test autonomous navigation algorithms with real UAV platforms in the real world. It becomes even more difficult when developing autonomous navigation algorithms based on deep learning techniques, since it requires to collect a large amount of annotated training data. To address such problem, we developed a simulation platform based on Unreal Engine, providing physically and visually realistic simulations, to validate and test navigation algorithms for Multi-rotor UAVs.
机译:在不使用extern定位信号的情况下开发自主导航算法是允许多转子过滤器在GNSS信号是一周或无效的复杂环境中飞行的键。然而,它是一种昂贵且耗时的过程,可以在现实世界中使用真正的UAV平台进行自主导航算法。在基于深度学习技术开发自主导航算法时,它变得更加困难,因为它需要收集大量注释的训练数据。为了解决此类问题,我们开发了一种基于虚幻引擎的仿真平台,提供物理和视觉上的仿真,用于验证和测试多转子无人机的导航算法。

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