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Collision Avoidance for Cooperative UAVs with Rolling Optimization Algorithm Based on Predictive State Space

机译:基于预测状态空间的滚动优化算法的协同无人机避碰

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摘要

Unmanned Aerial Vehicles (UAVs) have recently received notable attention because of their wide range of applications in urban civilian use and in warfare. With air traffic densities increasing, it is more and more important for UAVs to be able to predict and avoid collisions. The main goal of this research effort is to adjust real-time trajectories for cooperative UAVs to avoid collisions in three-dimensional airspace. To explore potential collisions, predictive state space is utilized to present the waypoints of UAVs in the upcoming situations, which makes the proposed method generate the initial collision-free trajectories satisfying the necessary constraints in a short time. Further, a rolling optimization algorithm (ROA) can improve the initial waypoints, minimizing its total distance. Several scenarios are illustrated to verify the proposed algorithm, and the results show that our algorithm can generate initial collision-free trajectories more efficiently than other methods in the common airspace.
机译:由于无人机在城市民用和战争中的广泛应用,近来受到了广泛的关注。随着空中交通密度的增加,无人机能够预测并避免碰撞变得越来越重要。这项研究工作的主要目标是调整协作型无人机的实时轨迹,以避免在三维空域中发生碰撞。为了探索潜在的碰撞,利用预测状态空间来表示无人机在即将到来的情况下的航路点,从而使该方法能够在短时间内生成满足必要约束的初始无碰撞轨迹。此外,滚动优化算法(ROA)可以改善初始航点,从而使其总距离最小。举例说明了几种情况,以验证所提出的算法,结果表明,与普通空域中的其他方法相比,我们的算法可以更有效地生成初始无碰撞轨迹。

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