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Integrating Safety-Aware Route Optimisation and Run-Time Safety Monitoring in Controlling Swarms of Drones

机译:将安全意识路线优化与运行时安全监控相结合,以控制无人机群

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Swarm of drones are increasingly deployed to perform a variety of critical missions such as surveillance, rescue in disaster areas etc. To guarantee success of a mission, the controlling software should pursue two goals. Firstly, it should ensure safety, i.e., guarantee collision avoidance. Secondly, it should prevent a premature depletion of the batteries of the drones by minimizing their travel paths. In this paper, we propose an approach that combines run-time safety monitoring and high performance evolutionary algorithm to predict dynamically emerging hazards. High performance of the route calculation algorithm allows us to ensure that the routes of drones are dynamically adjusted to avoid collisions while maintaining efficiency. The benchmarking of the proposed approach validates its efficiency and safety.
机译:越来越多的无人机被部署用于执行各种关键任务,例如监视,在灾区进行营救等。为了保证任务的成功,控制软件应追求两个目标。首先,它应确保安全,即确保避免碰撞。其次,应该通过最小化无人机的行进路径来防止无人机电池过早耗尽。在本文中,我们提出了一种将运行时安全监控和高性能进化算法相结合的方法来动态预测动态出现的危害。路线计算算法的高性能使我们能够确保无人驾驶飞机的路线得到动态调整,从而避免碰撞,同时保持效率。所提出方法的基准测试验证了其效率和安全性。

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