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Human following for mobile robots

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conference contribution
posted on 2022-07-20, 10:11 authored by Wenjuan ZhouWenjuan Zhou, Peter DickensonPeter Dickenson, Haibin CaiHaibin Cai, Baihua LiBaihua Li

Human following is an essential function in many robotic systems. Most of the existing human following algorithms are based on human tracking algorithms. However, in practical scenarios, the human subject might easily disappear due to occlusions and quick movements. In order to solve the problem of occlusion, this paper proposed a classification-based human following framework. After using a pretrained MobileNetV2 model to detect the human subjects, the robot will automatically train a classification model to identify the target person. In the end, the robot is controlled by some rule-based motion commands to follow the target human. Experimental results on several practical scenarios have demonstrated the effectiveness of the algorithm. 

History

School

  • Science
  • Sport, Exercise and Health Sciences

Department

  • Computer Science

Published in

Intelligent Robotics and Applications: 15th International Conference, ICIRA 2022, Harbin, China, August 1–3, 2022, Proceedings, Part I

Pages

660 - 668

Source

International Conference on Intelligent Robotics and Applications (ICIRA 2022)

Publisher

Springer

Version

  • AM (Accepted Manuscript)

Rights holder

© The Author(s), under exclusive license to Springer Nature Switzerland AG

Publisher statement

This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-13844-7_61. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms

Acceptance date

2022-06-13

Publication date

2022-08-04

Copyright date

2022

ISBN

9783031138430; 9783031138447

ISSN

0302-9743

eISSN

1611-3349

Book series

Lecture Notes in Computer Science (LNCS, volume 13455)

Language

  • en

Editor(s)

Honghai Liu; Zhouping Yin; Lianqing Liu; Li Jiang; Guoying Gu; Xinyu Wu; Weihong Ren

Location

Harbin, China

Event dates

1st August 2022 - 3rd August 2022

Depositor

Wenjuan Zhou. Deposit date: 19 July 2022

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