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

doi:10.1109/INFOCOMWKSHPS54753.2022.9798353

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

Department of Electrical and Computer Engineering - Communication, Control and Automation

Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review

1 Citation (Scopus)

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 language	English
Title of host publication	INFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops
Number of pages	2
Publisher	IEEE
Publication date	Jun 2022
ISBN (Electronic)	978-1-6654-0926-1
DOIs	https://doi.org/10.1109/INFOCOMWKSHPS54753.2022.9798353
Publication status	Published - Jun 2022
Event	IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2022 - Virtual, Online, United States Duration: 2 May 2022 → 5 May 2022

Conference

Conference	IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2022
Location	Virtual, Online
Country/Territory	United States
Period	02/05/2022 → 05/05/2022

Access to Document

10.1109/INFOCOMWKSHPS54753.2022.9798353

https://ieeexplore.ieee.org/document/9798353/authors

Cite this

@inproceedings{a278db7197d34bea936935fbd2f950ed,

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

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.",

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

year = "2022",

month = jun,

doi = "10.1109/INFOCOMWKSHPS54753.2022.9798353",

language = "English",

booktitle = "INFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops",

publisher = "IEEE",

note = "IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2022 ; Conference date: 02-05-2022 Through 05-05-2022",

}

Gu, X, Wang, X, Feng, Y, Long, Y, Mukherjee, M, Pan, Z, Guo, M & Zhang, Q 2022, Demo: TINGLE: Pushing Edge Intelligence in Synchronization and Useful Data Transfer for Human-Robotic Arm Interactions. in INFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops. IEEE, IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2022, United States, 02/05/2022. https://doi.org/10.1109/INFOCOMWKSHPS54753.2022.9798353

Demo: TINGLE: Pushing Edge Intelligence in Synchronization and Useful Data Transfer for Human-Robotic Arm Interactions. / Gu, Xinjie ; Wang, Xiaolong; Feng, Yuchen et al.
INFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops. IEEE, 2022.

Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Demo

T2 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2022

AU - Gu, Xinjie

AU - Wang, Xiaolong

AU - Feng, Yuchen

AU - Long, Yuzhu

AU - Mukherjee, Mithun

AU - Pan, Zhigeng

AU - Guo, Mian

AU - Zhang, Qi

PY - 2022/6

Y1 - 2022/6

N2 - 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.

AB - 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.

U2 - 10.1109/INFOCOMWKSHPS54753.2022.9798353

DO - 10.1109/INFOCOMWKSHPS54753.2022.9798353

M3 - Article in proceedings

BT - INFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops

PB - IEEE

Y2 - 2 May 2022 through 5 May 2022

ER -

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

Abstract

Conference

Access to Document

Fingerprint

Cite this