Optimized Task Offloading in UAV-Assisted Cloud Robotics

Abstract

In this paper, we consider a UAV-assisted cloud robotic network in which a set of robots is deployed to perform specific missions, e.g., surveillance and rescue, in an area where the communication condition is unfavorable for the robots. Data collected by a robot can be either offloaded to a MEC server or to a remote cloud through the UAVs or to a nearby robot for computation. We formulate this offloading problem as a combinatorial nonconvex problem. A joint scheme for offloading decision-making, robot-UAV association, and computational resource allocation is proposed using KKT conditions, Lagrangian dual decomposition, and the Proximal Policy Optimization method to obtain the solution to the formulated problem. The simulation results show our proposed algorithm achieves a solution close to the optimal solution and outperforms the baselines.