RAREST: Emulation of Augmented Reality Assisted Multi-UAV-UGV Systems

Abstract

AR-assisted multi-UAV-UGV systems are versatile robotic platforms for challenging missions. However, these systems face several challenges, such as energy constraints, limited computation capability, and intermittent network connectivity. In this paper, we present RAREST (AR Assisted GRound and AErial Sytem Twin), a digital twin (DT) framework for emulating such systems. RAREST simulates the CPU workload and energy consumption of each UAV based on different tasks, enables the cooperation and offloading between UAVs and UGVs, and provides an AR interface for human users to interact with the system. We describe the envisioned framework, its potential use cases, and its benefits over pure simulations. We also report our preliminary work simulating CPU workload and energy consumption for different object recognition tasks on UAVs and how this framework can be expanded and implemented in the future.