动态环境下无人机避碰速度方法的实现

V. Berdonosov, A. Zivotova, D. Zhuravlev, Zaw Htet Naing
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引用次数: 5

摘要

多架无人机在公共航空区域的位置增加了碰撞概率。自2015年以来,与避免此类碰撞有关的论文数量显著增加。大多数方法和算法都需要增加车载计算机系统的计算能力,这对于检测和跟踪动态威胁以及实施避碰机动是必不可少的。许多研究人员建议使用自动依赖监视系统(ADS-B)或类似物来减少检测和跟踪动态威胁的计算成本。计算成本也可以通过用解析算法代替数值算法来降低。本文提出了一种新的避碰机动选择与实施方法。利用ADS-B系统获得的2个或3个轨迹点来逼近无人机轨迹。然后,利用解析表达式,计算出可能发生碰撞的临界速度范围的两个截止值。由于临界速度交汇点和截止值的计算表达式采用解析形式表示,因此即使车载计算机系统的计算能力有限,计算时间也远远少于接收ADS-B数据的时间。因此,可以在每个接收新数据的周期更新计算,并且轨迹近似可以以直线为界。这种方法允许开发紧凑的避碰算法,甚至适用于大量无人机(超过几十架)。通过使用专门为此目的开发的软件系统进行建模来证明研究的充分性。
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Implementation of the Speed Approach for UAV Collision Avoidance in Dynamic Environment
Location of many UAV in a common aviation area increases collision probability. Since 2015 the number of papers related to the avoidance of such collisions has increased significantly. The most part of methods and algorithms require increasing computational capacity of on-board computer systems that is essential for detecting and tracking dynamic threats and implementing maneuvers of collision avoidance. Many researchers suggest the usage of automatic dependent surveillance system (ADS-B) or analogues to decrease computational costs for detecting and tracking dynamic threats. Computational costs can be also decreased via replacing numerical algorithms by analytical ones. In the paper a new method of selection and implementation of collision avoidance maneuvers is suggested. UAV trajectories are approximated by two or three trajectory points obtained from ADS-B system. Then, using analytical expressions, two cutoff values of the critical speed range, at which a collision is possible, are calculated. As calculation expressions for meeting points and cutoff values of the critical speed are represented in the analytical form, even if an on-board computer system has limited computational capacity, the time for calculation will be far less than the time of receiving data from ADS-B. For this reason, calculations can be updated at each cycle of new data receiving, and the trajectory approximation can be bounded by straight lines. Such an approach allows developing compact algorithm of collision avoidance, even for a significant number of UAVs (more than several dozens). Research adequacy is proved by modeling using a software system developed specifically for this purpose.
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