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A Cloud-Based Visual SLAM Framework for Low-Cost Agents

  • Jianhao JiaoEmail author
  • Peng Yun
  • Ming Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10528)

Abstract

Constrained by on-board resource, most of the low-cost robots could not autonomously navigate in unknown environments. In the latest years, cloud computing and storage has been developing rapidly, making it possible to offload parts of visual SLAM processing to a server. However, most of the cloud-based vSLAM frameworks are not suitable or fully tested for the applications of poor-equipped agents. In this paper, we describe an online localization service on a novel cloud-based framework, where the expensive map storage and global feature matching are provided as a service to agents. It enables a scenario that only sensor data collection is executed on agents, while the cloud aids the agents to localize and navigate. At the end, we evaluate the localization service quantitatively and qualitatively. The results indicate that the proposed cloud framework can fit the requirement of real-time applications.

Keywords

Cloud robotics Mobile robot Visual SLAM 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Robotics and Multi-perception Lab (RAM-LAB), Robotics InstituteThe Hong Kong University of Science and TechnologyHong KongChina

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