Autonomous Human Following Robot Based on Follow the Gap Method

Umut Uguzlar*, Enes Cansu, Emre Can Contarli, Volkan Sezer

*Corresponding author for this work

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

Abstract

With the recent advances in robotics and artificial intelligence, human-robot interaction has become increasingly important for various applications. Autonomous robots are required to detect humans, provide safety, and follow them in some cases. Several approaches have been developed for detecting and tracking humans. In this paper, we propose a new approach that fuses two different human detection and tracking algorithms, namely the RWTH Upper Body Detector and Joint Leg Tracker, to provide a more robust human detection. We then use nearest-neighbor data association and Extended Kalman Filter to track the human. We also modify and integrate the Follow the Gap Method obstacle avoidance algorithm into the human tracking task to ensure a safe path and heading angle towards the person. Our proposed approach uses a similar approach to Adaptive Cruise Control for the robot to follow the person from a desired distance. We evaluate the performance of the proposed approach by considering the tracking distance error and heading angle difference between the human and robot in different scenarios.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2023
EditorsAna C. Lopes, Gabriel Pires, Vitor H. Pinto, Jose L. Lima, Pedro Fonseca
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages139-144
Number of pages6
ISBN (Electronic)9798350301212
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2023 - Tomar, Portugal
Duration: 26 Apr 202327 Apr 2023

Publication series

Name2023 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2023

Conference

Conference2023 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2023
Country/TerritoryPortugal
CityTomar
Period26/04/2327/04/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Funding

ACKNOWLEDGMENT This work was supported by the Turkish Scientific and Technological Research Council (TUBITAK) under project no. 121E537.

FundersFunder number
Turkish Scientific and Technological Research Council
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu121E537

    Keywords

    • adaptive cruise control
    • autonomous robots
    • human detection
    • human following
    • local planning

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