A Long-Short-Term Memory-Based Model for Kinesthetic Data Reduction

TY - JOUR

T1 - A Long-Short-Term Memory-Based Model for Kinesthetic Data Reduction

AU - Deng, Qifang

AU - Mahmoodi, Toktam

AU - Aghvami, Abdol-Hamid

N1 - Publisher Copyright: © 2014 IEEE.

PY - 2023/10/1

Y1 - 2023/10/1

N2 - This article proposes a novel mathematical model for teleoperation over communication networks. For teleoperation over a communication network, a high packet rate can result in inefficient data transmission and cross-traffic problems, leading to extra delay and jitter. This article proposes an long short-term memory (LSTM)-based mathematical model which focuses on kinesthetic data reduction without loss of transparency during the transmission process through joint training combined with haptic data and perceptual deadband. Since the LSTM network can deal with a time series of haptic data, we further test the system performance through practically collected data. We investigate the packet rate and perceptual transparency of the proposed mathematical model by comparing with the conventional deadband. Additionally, we compare the proposed mathematical model with the perceptual deadband-based codecs. Simulation results show that the proposed solution further reduces the packet rate when dealing with haptic data without noticeable distortion. Also, comparing with the current just noticeable difference perceptual threshold, the proposed mathematical model helps improve the practicality of the bilateral teleoperation system without losing transparency.

AB - This article proposes a novel mathematical model for teleoperation over communication networks. For teleoperation over a communication network, a high packet rate can result in inefficient data transmission and cross-traffic problems, leading to extra delay and jitter. This article proposes an long short-term memory (LSTM)-based mathematical model which focuses on kinesthetic data reduction without loss of transparency during the transmission process through joint training combined with haptic data and perceptual deadband. Since the LSTM network can deal with a time series of haptic data, we further test the system performance through practically collected data. We investigate the packet rate and perceptual transparency of the proposed mathematical model by comparing with the conventional deadband. Additionally, we compare the proposed mathematical model with the perceptual deadband-based codecs. Simulation results show that the proposed solution further reduces the packet rate when dealing with haptic data without noticeable distortion. Also, comparing with the current just noticeable difference perceptual threshold, the proposed mathematical model helps improve the practicality of the bilateral teleoperation system without losing transparency.

KW - Algorithm

KW - Haptic Communication

KW - Kinesthetic Data

KW - LSTM Networks

KW - Bilateral Teleoperation

UR - http://www.scopus.com/inward/record.url?scp=85159692304&partnerID=8YFLogxK

U2 - 10.1109/JIOT.2023.3271603

DO - 10.1109/JIOT.2023.3271603

M3 - Article

VL - 10

SP - 16975

EP - 16988

JO - IEEE Internet of Things Journal

JF - IEEE Internet of Things Journal

IS - 19

ER -