Demo: TINGLE: Pushing Edge Intelligence in Synchronization and Useful Data Transfer for Human-Robotic Arm Interactions

Xinjie Gu, Xiaolong Wang, Yuchen Feng, Yuzhu Long, Mithun Mukherjee, Zhigeng Pan, Mian Guo, Qi Zhang

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Abstract

This demo presents a lightweight framework for the remote operation of human-robot interactions. As always, proper synchronization between the human (master) and the robot (controlled) is a critical issue during manipulation. In this experiment, we present an end-to-end synchronous system to establish near real-time maneuvering. Moreover, by leveraging the devices' limited yet available computational capabilities in master and controlled domains, we aim to apply edge intelligence to determine the amount of data required for mimicking the human's hand movement before wireless transmission to the controlled domain. We observe from extensive experiment results that our proposed TINGLE demonstrates a noticeable performance with fewer missing movements in the controlled domain than baselines.

Original languageEnglish
Title of host publicationINFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops
Number of pages2
PublisherIEEE
Publication dateJun 2022
ISBN (Electronic)978-1-6654-0926-1
DOIs
Publication statusPublished - Jun 2022
EventIEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2022 - Virtual, Online, United States
Duration: 2 May 20225 May 2022

Conference

ConferenceIEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2022
LocationVirtual, Online
Country/TerritoryUnited States
Period02/05/202205/05/2022

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