Autonomous Human Following Robot Based on Follow the Gap Method

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

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Özet

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.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığı2023 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2023
EditörlerAna C. Lopes, Gabriel Pires, Vitor H. Pinto, Jose L. Lima, Pedro Fonseca
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar139-144
Sayfa sayısı6
ISBN (Elektronik)9798350301212
DOI'lar
Yayın durumuYayınlandı - 2023
Etkinlik2023 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2023 - Tomar, Portugal
Süre: 26 Nis 202327 Nis 2023

Yayın serisi

Adı2023 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2023

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???event.eventtypes.event.conference???2023 IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2023
Ülke/BölgePortugal
ŞehirTomar
Periyot26/04/2327/04/23

Bibliyografik not

Publisher Copyright:
© 2023 IEEE.

Finansman

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

FinansörlerFinansör numarası
Turkish Scientific and Technological Research Council
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu121E537

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