Consider a set of landmarks that are distributed in an emergency scene and each needs a specific number of robots in its vicinity. This paper presents a two-stage framework for deploying robots autonomously for such scenarios. In the first stage, a Two-hop Cooperative Virtual Force Robot Deployment (Two-hop COVER) technique is employed. It expedites the deployment process by establishing a cooperative relationship between robots and neighboring landmarks. Two-hop communication is utilized as well to reduce the deployment time and traveled distance by robots to satisfy the mission requirements and optimize the deployment process. However, in certain scenarios, Two-hop COVER may not achieve full demand satisfaction. Therefore, the second stage, called Trace Fingerprint is invoked to guarantee full satisfaction. Finally, a fairness-aware version of Two-hop COVER is presented to consider scenarios in which the mission requirements are greater than the available resources (i.e. robots) and hence, the fairness-aware approach dispatches robots in proportion to each landmark's need. Extensive simulation experiments have been carried out to assess the performance of the proposed framework. The simulation results demonstrate the effectiveness of the proposed approaches considering several performance factors, such as total travelled distance, total exchanged messages, total deployment time, and Jain's fairness index.

考虑一组分布在紧急情况下的地标，每个地标在其附近都需要特定数量的机器人。本文提出了一种针对这种情况自动部署机器人的两阶段框架。在第一阶段，采用了两步协作虚拟力机器人部署（两步COVER）技术。它通过在机器人和邻近地标之间建立协作关系来加快部署过程。还利用两跳通信来减少机器人的部署时间和行进距离，从而满足任务要求并优化部署过程。但是，在某些情况下，两跳COVER可能无法完全满足需求。因此，调用第二阶段称为“跟踪指纹”以确保完全满意。最后，提出了两步COVER的公平意识版本，以考虑任务需求大于可用资源（即机器人）的情况，因此，基于公平意识的方法会根据每个地标的需求分配机器人。已经进行了广泛的仿真实验，以评估所提出框架的性能。仿真结果证明了该方法的有效性，该方法考虑了多个性能因素，例如总行进距离，总交换消息，总部署时间和Ja那教公平指数。已经进行了广泛的仿真实验，以评估所提出框架的性能。仿真结果证明了该方法的有效性，该方法考虑了多个性能因素，例如总行进距离，总交换消息，总部署时间和Ja那教公平指数。已经进行了广泛的仿真实验，以评估所提出框架的性能。仿真结果证明了该方法的有效性，该方法考虑了多个性能因素，例如总行进距离，总交换消息，总部署时间和Ja那教公平指数。