RAREST:增强现实辅助多uav - ugv系统仿真

Benjamin P. Carlson, Chenyang Wang, Qifeng Han
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引用次数: 0

摘要

ar辅助的多无人机- ugv系统是用于具有挑战性任务的多功能机器人平台。然而,这些系统面临着一些挑战,如能源限制、有限的计算能力和间歇性的网络连接。在本文中,我们提出了RAREST (AR辅助地面和空中系统双胞胎),这是一个用于模拟此类系统的数字双胞胎(DT)框架。RAREST基于不同的任务,模拟了每架无人机的CPU工作负载和能耗,实现了无人机与ugv之间的协作和卸载,并为人类用户提供了与系统交互的AR界面。我们描述了设想的框架,它的潜在用例,以及它相对于纯模拟的好处。我们还报告了我们在无人机上模拟不同目标识别任务的CPU工作负载和能耗的初步工作,以及该框架如何在未来扩展和实施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RAREST: Emulation of Augmented Reality Assisted Multi-UAV-UGV Systems
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.
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