A SLAM-Based Localization and Navigation System for Social Robots: The Pepper Robot Case-Reference-Cited by-同舟云学术

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

Published:2023-01-23 Issue:2 Volume:11 Page:158
ISSN:2075-1702
Container-title:Machines
language:en
Short-container-title:Machines

Author:

Alhmiedat Tareq¹²^ORCID,Marei Ashraf M.²³,Messoudi Wassim⁴,Albelwi Saleh²⁴,Bushnag Anas³,Bassfar Zaid¹^ORCID,Alnajjar Fady⁵^ORCID,Elfaki Abdelrahman Osman⁴

Affiliation:

1. Department of Information Technology, Faculty of Computers & Information Technology, University of Tabuk, Tabuk 71491, Saudi Arabia

2. Artificial Intelligence and Sensing Technologies (AIST) Research Center, University of Tabuk, Tabuk 41491, Saudi Arabia

3. Department of Computer Engineering, Faculty of Computers & Information Technology, University of Tabuk, Tabuk 71491, Saudi Arabia

4. Department of Computer Science, Faculty of Computers & Information Technology, University of Tabuk, Tabuk 71491, Saudi Arabia

5. College of Information Technology, United Arab Emirates University, Al Ain 15551, United Arab Emirates

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%.

Funder

University of Tabuk

Publisher

MDPI AG

Subject

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

Link

https://www.mdpi.com/2075-1702/11/2/158/pdf

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