5G-based Low-Latency Teleoperation: Two-way Timeout Approach

Kizilkaya, B. , Popoola, O. , Zhao, G. and Imran, M. A. (2023) 5G-based Low-Latency Teleoperation: Two-way Timeout Approach. In: Towards Autonomous Robotic Systems (TAROS) 2023 Conference, Cambridge, United Kingdom, 13-15 September 2023, pp. 470-481. ISBN 9783031433597 (doi: 10.1007/978-3-031-43360-3_38)

Abstract

Recent advances in communications and robotics enable myriad teleoperation applications, empowering real-time remote operation in various application areas such as healthcare, education, manufacturing, and aerial manipulation. The main problems in teleoperation systems are the time delay and packet loss caused by poor network conditions. Ultra-reliable Low-Latency Communication (URLLC), one of the key services of fifth-generation cellular communications (5G), is expected to enable real-time teleoperation by mitigating latency and reliability issues of pre-5G communications. In this study, we develop a 5G-enabled teleoperation testbed to conduct experiments on communication latency and packet loss, demonstrating the current capabilities of 5G communications for teleoperation applications. Furthermore, we propose a two-way timeout approach to reduce the communication latency. The proposed approach reduces the end-to-end (E2E) latency by limiting the waiting time for new packet reception. Extensive latency and packet loss experiments are conducted to demonstrate the superiority of the proposed approach compared to the benchmark approach without a timeout. The experimental results corroborate that the proposed approach can reduce E2E latency by up to 65% and improves overall reliability.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Zhao, Dr Guodong and Popoola, Dr Olaoluwa and Imran, Professor Muhammad and KIZILKAYA, BURAK
• Authors: Kizilkaya, B., Popoola, O., Zhao, G., and Imran, M. A.
• College/School: College of Science and Engineering > School of Engineering; College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• ISSN: 0302-9743
• ISBN: 9783031433597
• Copyright Holders: Copyright © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
• First Published: First published in Towards Autonomous Robotic Systems. TAROS 2023. Lecture Notes in Computer Science 14136:470-481
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

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