Swarm robotics is envisioned to automate a large number of dirty, dangerous, and dull tasks. Robots have limited energy, computation capability, and communication resources. Therefore, current swarm robotics have a small number of robots, which can only provide limited spatio-temporal information. In this paper, we propose to leverage the mobile edge computing to alleviate the computation burden. We develop an effective solution based on a mobility-aware deep reinforcement learning model at the edge server side for computing scheduling and resource. Our results show that the proposed approach can meet delay requirements and guarantee computation precision by using minimum robot energy.

翻译：群体机器人技术旨在自动化大量脏乱、危险及乏味的任务。机器人具备有限的能量、计算能力和通信资源。因此，当前群体机器人系统中机器人数量较少，仅能提供有限的时空信息。本文提出利用移动边缘计算来减轻计算负担。我们开发了一种基于边缘服务器端移动感知深度强化学习模型的有效解决方案，用于计算调度与资源分配。实验结果表明，所提方法能够在最小化机器人能耗的同时满足延迟要求并保证计算精度。