Unmanned Aerial Vehicle (UAVs) have become very popular in the last decade due to some advantages such as strong terrain adaptation, low cost, zero casualties, and so on. One of the most interesting advances in this field is the automation of mission planning (task allocation) and real-time replanning, which are highly useful to increase the autonomy of the vehicle and reduce the operator workload. These automated mission planning and replanning systems require a Human Computer Interface (HCI) that facilitates the visualization and selection of plans that will be executed by the vehicles. In addition, most missions should be assessed before their real-life execution. This paper extends QGroundControl, an open-source simulation environment for flight control of multiple vehicles, by adding a mission designer that permits the operator to build complex missions with tasks and other scenario items; an interface for automated mission planning and replanning, which works as a test bed for different algorithms, and a Decision Support System (DSS) that helps the operator in the selection of the plan. In this work, a complete guide of these systems and some practical use cases are provided.

翻译：无人机（UAV）近十年来因地形适应性强、成本低、零伤亡等优势而广泛应用。该领域最引人注目的进展之一是任务规划（任务分配）的自动化与实时重规划技术，这对提升飞行器自主性、降低操作员负担具有重要价值。此类自主任务规划与重规划系统需要人机交互界面（HCI）来辅助操作员可视化并选择由飞行器执行的方案。此外，大多数任务在实际执行前需进行评估。本文对QGroundControl（一种用于多飞行器飞行控制的开源仿真环境）进行了功能扩展：增加任务设计模块，支持操作员构建包含任务及其他场景元素的复杂任务体系；开发自主任务规划与重规划接口，可作为不同算法的测试平台；构建决策支持系统（DSS），协助操作员优化方案选择。本研究提供了上述系统的完整指南及若干实际应用案例。