Cellular-enabled collaborative robots are becoming paramount in Search-and-Rescue (SAR) and emergency response. Crucially dependent on resilient mobile network connectivity, they serve as invaluable assets for tasks like rapid victim localization and the exploration of hazardous, otherwise unreachable areas. However, their reliance on battery power and the need for persistent, low-latency communication limit operational time and mobility. To address this, and considering the evolving capabilities of 5G/6G networks, we propose a novel SAR framework that includes Mission Planning and Mission Execution phases and that optimizes robot deployment. By considering parameters such as the exploration area size, terrain elevation, robot fleet size, communication-influenced energy profiles, desired exploration rate, and target response time, our framework determines the minimum number of robots required and their optimal paths to ensure effective coverage and timely data backhaul over mobile networks. Our results demonstrate the trade-offs between number of robots, explored area, and response time for wheeled and quadruped robots. Further, we quantify the impact of terrain elevation data on mission time and energy consumption, showing the benefits of incorporating real-world environmental factors that might also affect mobile signal propagation and connectivity into SAR planning. This framework provides critical insights for leveraging next-generation mobile networks to enhance autonomous SAR operations.

翻译：蜂窝网络协作机器人在搜救与应急响应中正变得至关重要。它们高度依赖稳健的移动网络连接，在快速定位受困者以及探索危险且难以抵达的区域等任务中成为宝贵资产。然而，其对电池供电的依赖以及对持续低延迟通信的需求，限制了其运行时间和移动性。为解决这一问题，并考虑到5G/6G网络不断演进的能力，我们提出了一种新颖的搜救框架，该框架包含任务规划与任务执行两个阶段，并对机器人部署进行优化。通过综合考虑探索区域大小、地形高程、机器人集群规模、受通信影响的能量分布、期望探索速率以及目标响应时间等参数，我们的框架能够确定所需机器人的最小数量及其最优路径，以确保通过移动网络实现有效覆盖和及时的数据回传。我们的研究结果揭示了轮式机器人与四足机器人在机器人数量、探索区域和响应时间之间的权衡关系。此外，我们量化了地形高程数据对任务时间和能量消耗的影响，证明了将可能影响移动信号传播与连接性的真实环境因素纳入搜救规划的益处。该框架为利用下一代移动网络增强自主搜救操作提供了关键见解。