Obtaining a ROS-Based Face Recognition and Object Detection: Hardware and Software Issues

Petri Oksa, Tero Salminen, Tarmo Lipping

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

This paper presents solutions for methodological issues that can occur when obtaining face recognition and object detection for a ROS-based (Robot Operating System) open-source platform. Ubuntu 18.04, ROS Melodic and Google TensorFlow 1.14 are used in programming the software environment. TurtleBot2 (Kobuki) mobile robot with additional onboard sensors are used to conduct the experiments. Entire system configurations and specific hardware modifications that were proved mandatory to make out the system functionality are also clarified. Coding (e.g., Python) and sensors installations are detailed both in onboard and remote laptop computers. In experiments, TensorFlow face recognition and object detection are examined by using the TurtleBot2 robot. Results show how objects and faces were detected when the robot is navigating in the previously 2D mapped indoor environment.

Original languageEnglish
Title of host publicationProceedings of 6th International Congress on Information and Communication Technology, ICICT 2021
EditorsXin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi
PublisherSpringer
Pages949-962
Number of pages14
ISBN (Print)9789811623769
DOIs
Publication statusPublished - 2022
Publication typeA4 Article in a conference publication
EventInternational Congress on Information and Communication Technology -
Duration: 25 Feb 202226 Feb 2022

Publication series

NameLecture Notes in Networks and Systems
Volume235
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceInternational Congress on Information and Communication Technology
Period25/02/2226/02/22

Keywords

  • ROS
  • Ubuntu
  • Object detection
  • Face recognition
  • 3D sensor
  • LiDAR

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications

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