低资源硬件中SLAM的研究进展

Ismail Ismail
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引用次数: 3

摘要

SLAM的许多研究都是针对台式机或笔记本电脑的。安装在像先锋这样的机器人平台上,这些高计算能力的硬件完成SLAM中的所有处理。此外,SLAM算法利用GPU的能力在地图重建中提供深入的细节。然而,在没有高计算能力硬件优势的小型机器人中部署SLAM是可取的。由于电源有限,计算能力低,单板计算机通常是小型机器人的主板。因此,考虑针对这样一个系统的SLAM设计方案是很重要的。考虑到这一点,目前的工作提出了在低资源硬件SLAM的调查论文。当前这项工作需要回答的主要问题是“研究人员在实现SLAM时如何处理硬件限制?”最后提出了一种基于分类的方法来解决这一问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Survey of SLAM in Low-Resourced Hardware
Many of researches in SLAM are targeting desktops or laptop computers. Mounted in a robot platform such as Pioneer, these high computational power hardware do all the processing in SLAM. Still others, SLAM algorithms exploit GPU power to provide deep details in map reconstruction. Yet, it is desirable to deploy SLAM in a small robot without advantages from high computational power hardware. Single board computer with limited power supply and low computational power is frequently the main board available in a small robot. Therefore, it is important to consider the design solution of SLAM that targets such a system. With this in mind, current work presents a survey paper of SLAM in low-resource hardware. The main question to be answered with this current work is "How researchers deal with hardware limitation when implementing SLAM?" Classification based on a method to tackle the problem is presented as the conclusion of this paper.
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