Fog computing-enabled robot simultaneous localization and mapping

Yang YANG; Kai LI; Haidong XU; Huajun WANG; Kunlun WANG; Jian LI; Mingtuo ZHOU

doi:10.11959/j.issn.2096-3750.2018.00050

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Fog computing-enabled robot simultaneous localization and mapping

Theory and Technology | 更新时间：2024-06-05

- Fog computing-enabled robot simultaneous localization and mapping
- Chinese Journal on Internet of Things Vol. 2, Issue 2, Pages: 33-40(2018)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-3750.2018.00050
  CLC： TP393
- Published：30 June 2018，
  
  Published Online：2018-06，
- 稿件说明：
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YANG YANG, KAI LI, HAIDONG XU, et al. Fog computing-enabled robot simultaneous localization and mapping. [J]. Chinese journal on internet of things, 2018, 2(2): 33-40.
DOI：

YANG YANG, KAI LI, HAIDONG XU, et al. Fog computing-enabled robot simultaneous localization and mapping. [J]. Chinese journal on internet of things, 2018, 2(2): 33-40. DOI： 10.11959/j.issn.2096-3750.2018.00050.

摘要

机器人探索预先未知的环境时通常需要同步定位和地图构建（SLAM），例如，在救援场景中，可以利用雾计算这种新兴的计算模式来实现更快、更精确、更节能的机器人SLAM。基于此，提出了雾计算赋能机器人SLAM的框架设计，并分析了其面临的挑战，最后通过真实试验床演示了该框架设计。

Abstract

Robot simultaneous localization and mapping (SLAM) is often required when robots are used to explore prior-unknown environment

e.g.

in rescue scenarios.Fog computing

an emerging computing mode could be used to enable faster

more accurate

speedier

and energy-saved robot SLAM.The framework of fog-enabled robot SLAM addressing was proposed

and challenges it faced were analyzed.Finally

technologies by real implementation of testbed were demonstrated.

关键词

雾计算机器人同步定位和地图构建

Keywords

fog computingrobotsimultaneous location and mapping

references

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