面向SLAM应用的嵌入式系统架构
Embedded Systems Architecture for SLAM Applications
摘要：
近年来，我们观察到自动驾驶汽车、机器人技术、虚拟现实和增强现实的快速崛起有着明显的趋势。支持这些应用的核心技术，即同时定位与地图构建（SLAM），带来了两个主要挑战：首先，这些工作负载是计算密集型的，并且它们通常具有实时要求;其次，这些工作负载在电池供电的移动设备上运行，能量预算有限。简而言之，这些挑战的本质是在提高性能的同时降低能耗，这是传统智慧中两个相当矛盾的目标。在本文中，我们将仔细研究最先进的同时定位与地图构建（SLAM）工作负载，特别是这些工作负载在移动设备上的表现。基于研究结果，我们提出了一种移动架构，以提高移动设备上的SLAM性能。
英文摘要：
In recent years, we have observed a clear trend in the rapid rise of autonomous vehicles, robotics, virtual reality, and augmented reality. The core technology enabling these applications, Simultaneous Localization And Mapping (SLAM), imposes two main challenges: first, these workloads are computationally intensive and they often have real-time requirements; second, these workloads run on battery-powered mobile devices with limited energy budget. In short, the essence of these challenges is that performance should be improved while simultaneously reducing energy consumption, two rather contradicting goals by conventional wisdom. In this paper, we take a close look at state-of-the-art Simultaneous Localization And Mapping (SLAM) workloads, especially how these workloads behave on mobile devices. Based on the results, we propose a mobile architecture to improve SLAM performance on mobile devices.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
