In this demo work we develop a method to plan and coordinate a multi-agent team to gather information on demand. The data is periodically requested by a static Operation Center (OC) from changeable goals locations. The mission of the team is to reach these locations, taking measurements and delivering the data to the OC. Due to the limited communication range as well as signal attenuation because of the obstacles, the agents must travel to the OC, to upload the data. The agents can play two roles: ones as workers gathering data, the others as collectors traveling invariant paths for collecting the data of the workers to re-transmit it to the OC. The refreshing time of the delivered information depends on the number of available agents as well as of the scenario. The proposed algorithm finds out the best balance between the number of collectors-workers and the partition of the scenario into working areas in the planning phase, which provides the minimum refreshing time and will be the one executed by the agents.

翻译：在本演示工作中，我们开发了一种用于规划与协调多智能体团队按需收集信息的方法。静态操作中心（OC）会从可变的目标位置周期性请求数据。团队的任务是抵达这些位置进行测量，并将数据交付至OC。由于通信范围受限及障碍物导致的信号衰减，智能体必须移动至OC才能上传数据。智能体可扮演两种角色：一类作为采集数据的工作节点，另一类作为沿固定路径移动的收集节点，负责收集工作节点的数据并重新传输至OC。所交付信息的刷新时间取决于可用智能体数量及场景条件。所提算法在规划阶段可找出收集节点与工作节点数量之间的最优平衡，以及对场景工作区域的划分方案，从而提供最小刷新时间，该方案将由智能体执行。