A simple CSP-based model for Unmanned Air Vehicle Mission Planning

Cristian Ramírez-Atencia, Gema Bello Orgaz, M. Rodríguez-Moreno, David Camacho
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引用次数: 8

Abstract

The problem of Mission Planning for a large number of Unmanned Air Vehicles (UAV) can be formulated as a Temporal Constraint Satisfaction Problem (TCSP). It consists on a set of locations that should visit in different time windows, and the actions that the vehicle can perform based on its features such as the payload, speed or fuel capacity. In this paper, a temporal constraint model is implemented and tested by performing Backtracking search in several missions where its complexity has been incrementally modified. The experimental phase consists on two different phases. On the one hand, several mission simulations containing (n) UAVs using different sensors and characteristics located in different waypoints, and (m) requested tasks varying mission priorities have been carried out. On the other hand, the second experimental phase uses a backtracking algorithm to look through the whole solutions space to measure the scalability of the problem. This scalability has been measured as a relation between the number of tasks to be performed in the mission and the number of UAVs needed to perform it.
基于简单csp的无人机任务规划模型
针对大量无人机的任务规划问题可以归结为一个时间约束满足问题。它包括一组应该在不同时间窗口访问的地点,以及车辆可以根据其特征(如有效载荷、速度或燃料容量)执行的动作。本文实现了一个时间约束模型,并通过在多个任务中执行回溯搜索来测试该模型的复杂度。实验阶段包括两个不同的阶段。一方面,几个任务模拟包含(n)无人机使用不同的传感器和特性位于不同的航路点,(m)请求任务不同的任务优先级已经进行。另一方面,第二个实验阶段使用回溯算法来查看整个解决方案空间,以测量问题的可伸缩性。这种可扩展性已被衡量为任务中要执行的任务数量与执行任务所需的无人机数量之间的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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