面向自主与有人驾驶无人机的无碰撞轨迹研究
Toward collision-free trajectory for autonomous and pilot-controlled unmanned aerial vehicles
AI总结：
本文提出基于电子显形信息的无人机感知碰撞管理方法，利用反应式几何冲突检测与解决技术生成时间最优规避机动，在无需复杂传感器和预先训练的情况下实现动态空域中无人机与有人机的碰撞避免。
摘要：
对于作为安全关键系统的无人机而言，机载探测与规避（DAA）技术的需求日益增长，原因在于无人机具有多自由度的高机动性以及所部署非结构化环境的复杂性，因此需要 i) 看见、感知或探测冲突交通或迫近的非合作威胁，并随后 ii) 根据自主等级采取适当行动以避免碰撞。随着密集空中交通环境中多样化无人机应用大规模增长，以灵活且同时完成多个复杂任务集群，利用智能自主方法将无人机交通管理（UTM）系统与空中交通管理（ATM）系统安全高效地集成已成为一项新兴需求。过去几年中，在探测航空航天中存在的无人机、识别它们以及确定其现有飞行路径方面已取得重大进展。本研究进一步利用 PilotAware Ltd 提供的电子显形（EC）信息，开发了一种先进的碰撞管理方法——无人机感知碰撞管理（DACM）——该方法能够采用反应式几何冲突检测与解决（CDR）技术，确定并执行多种时间最优的规避碰撞（CA）机动。DACM 方法的优点已通过大量仿真和真实世界外场测试得到验证，用于避免无人机与有人驾驶飞机之间的空中相撞（MAC）。结果表明，所提出的方法能够在高度动态的航空航天环境中成功避免碰撞，同时限制对原始轨迹的偏离，且无需复杂传感器和预先训练。
英文摘要：
For drones, as safety-critical systems, there is an increasing need for onboard detect & avoid (DAA) technology i) to see, sense or detect conflicting traffic or imminent non-cooperative threats due to their high mobility with multiple degrees of freedom and the complexity of deployed unstructured environments, and subsequently ii) to take the appropriate actions to avoid collisions depending upon the level of autonomy. The safe and efficient integration of UAV traffic management (UTM) systems with air traffic management (ATM) systems, using intelligent autonomous approaches, is an emerging requirement where the number of diverse UAV applications is increasing on a large scale in dense air traffic environments for completing swarms of multiple complex missions flexibly and simultaneously. Significant progress over the past few years has been made in detecting UAVs present in aerospace, identifying them, and determining their existing flight path. This study makes greater use of electronic conspicuity (EC) information made available by PilotAware Ltd in developing an advanced collision management methodology -- Drone Aware Collision Management (DACM) -- capable of determining and executing a variety of time-optimal evasive collision avoidance (CA) manoeuvres using a reactive geometric conflict detection and resolution (CDR) technique. The merits of the DACM methodology have been demonstrated through extensive simulations and real-world field tests in avoiding mid-air collisions (MAC) between UAVs and manned aeroplanes. The results show that the proposed methodology can be employed successfully in avoiding collisions while limiting the deviation from the original trajectory in highly dynamic aerospace without requiring sophisticated sensors and prior training.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
