Resource Utilization Prediction Model for SLAM Offload to Edge

Koki Nagahama, Yoichi Ishiwata, Midori Sugaya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In recent years, the use of autonomous mobile robots has increased. SLAM (Simultaneous Localization and Mapping) technology is where an autonomous mobile robot estimates its own position and simultaneously maps the surrounding environment. It is widely used in robots that require autonomous movement. However, it is heavily burdened by computational tasks related to various types of image processing and calculations of physical environment recognition, which makes the system slow down due to limited hardware resources such as embedded systems. Various offload methods have been proposed, however they have not been applied to Robot Operating System (ROS) + SLAM applications and there are few examples of robot verification. To avoid the heavy load on the devices, we propose a method that takes the heavily load to the edge by using the prediction model based on the system resource information for a certain period related to SLAM processing. Based on preliminary experiences, we firstly develop a prediction model using system resource consumption data obtained from an actual SLAM execution and evaluate the prediction accuracy. The result shows that the accuracy varies as memory consumption increases, however the accuracy was high and useful in determining offload timing.

Original languageEnglish
Title of host publicationProceedings - 2020 8th International Symposium on Computing and Networking Workshops, CANDARW 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages100-105
Number of pages6
ISBN (Electronic)9781728199191
DOIs
Publication statusPublished - 2020 Nov
Event8th International Symposium on Computing and Networking Workshops, CANDARW 2020 - Virtual, Naha, Japan
Duration: 2020 Nov 242020 Nov 27

Publication series

NameProceedings - 2020 8th International Symposium on Computing and Networking Workshops, CANDARW 2020

Conference

Conference8th International Symposium on Computing and Networking Workshops, CANDARW 2020
CountryJapan
CityVirtual, Naha
Period20/11/2420/11/27

Keywords

  • Applications
  • Memory prediction model
  • Offload
  • Resource usage model
  • ROS
  • SLAM

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Computational Mathematics
  • Control and Optimization

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