A SLAM-Based Localization and Navigation System for Social Robots: The Pepper Robot Case

Tareq Alhmiedat, Ashraf M. Marei, Wassim Messoudi, Saleh Albelwi, Anas Bushnag, Zaid Bassfar, Fady Alnajjar, Abdelrahman Osman Elfaki

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Robot navigation in indoor environments has become an essential task for several applications, including situations in which a mobile robot needs to travel independently to a certain location safely and using the shortest path possible. However, indoor robot navigation faces challenges, such as obstacles and a dynamic environment. This paper addresses the problem of social robot navigation in dynamic indoor environments, through developing an efficient SLAM-based localization and navigation system for service robots using the Pepper robot platform. In addition, this paper discusses the issue of developing this system in a way that allows the robot to navigate freely in complex indoor environments and efficiently interact with humans. The developed Pepper-based navigation system has been validated using the Robot Operating System (ROS), an efficient robot platform architecture, in two different indoor environments. The obtained results show an efficient navigation system with an average localization error of 0.51 m and a user acceptability level of 86.1%.

Original languageEnglish
Article number158
JournalMachines
Volume11
Issue number2
DOIs
Publication statusPublished - Feb 2023

Keywords

  • Pepper robot
  • Robot Operating System (ROS)
  • SLAM
  • map production
  • robot navigation
  • social robot

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science (miscellaneous)
  • Mechanical Engineering
  • Control and Optimization
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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