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Performance Improvement of Multi-Robot Data Transmission in Aggregated Robot Processing Architecture with Caches and QoS Balancing Optimization 査読有り国際誌

Jalil A., Kobayashi J., Saitoh T.

Robotics 12 ( 3 ) 2023年06月

記述言語：英語掲載種別：研究論文（学術雑誌）

Robot Operating System 2 (ROS 2) is a robotic software that uses a set of Quality of Service (QoS) policies to manage the quality of robot data transmissions in a network, such as the RELIABLE and KEEP_LAST options. In ROS 2 node communication, the RELIABLE connection guarantees that all message data can be properly sent from the publisher to the subscriber. However, strict reliability is not guaranteed if the RELIABLE connection uses the KEEP_LAST option to transmit the robot data in the publish–subscribe communication. This study aims to analyze the efficiency of local cache, cache control, and QoS balancing optimization to improve ROS 2 node communication when using the RELIABLE and KEEP_LAST options to transmit multi-robot data in Aggregated Robot Processing (ARP) architecture. Our idea in local cache and cache control is to streamline the sensor data output before processing it when the sensor device produces the data with the same value in a row. Furthermore, QoS balancing optimization aims to balance the DEPTH and DEADLINE QoS configuration to determine the rates and buffer size in ROS 2 node communication. This study shows that combining local cache and QoS balancing optimization improves multi-robot data transmission and cooperation in ARP architecture.

DOI： 10.3390/robotics12030087

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85163380224&origin=inward

Optimization Algorithm for Balancing QoS Configuration in Aggregated Robot Processing Architecture 査読有り国際誌

Jalil A., Kobayashi J., Saitoh T.

Proceedings of International Conference on Artificial Life and Robotics 928 - 932 2023年01月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Quality of Service (QoS) manages the data traffic to reduce packet loss, latency, and jitter in the network. This study aims to design an optimization algorithm to find the balance of QoS configuration to set the rates and buffer size while the robot data processes are communicated in the Aggregated Robot Processing (ARP) architecture. This study implements optimization to manage the DEPTH and DEADLINE QoS configuration in Robot Operating System 2 (ROS 2) node communication. Unbalancing DEPTH and DEADLINE configurations can affect the high latency time of message data transmission and packet loss in RELIABLE connections. The results of this study show that the optimization algorithm can determine the optimal value of DEPTH and DEADLINE by balancing the QoS configuration to improve the robot data transmission in the ARP architecture.

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85149458445&origin=inward

QoS Balancing Optimization in Aggregated Robot Processing Architecture: Rate and Buffer 査読有り国際誌

Jalil Abdul, Kobayashi Jun, Saitoh Takeshi

Journal of Advances in Artificial Life Robotics ( 株式会社 ALife Robotics ) 3 ( 4 ) 209 - 213 2023年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

This study developed an optimization algorithm to balance the Quality of Service (QoS) rates and buffer size for robot data communication in the Aggregated Robot Processing (ARP) architecture. Robot Operating System 2 (ROS 2) is robotic software that uses a set of QoS policies to control the quality of data transmission in robotic networks, such as DEADLINE to determine the rates, and DEPTH to determine the buffer size. An unbalanced DEADLINE and DEPTH configuration in ROS 2 node communication can result in high packet latency and packet loss in RELIABLE connections. This happens when the DEADLINE sets the rates at high frequencies, and the DEPTH sets the buffers with small sizes. The results of this study show that the optimization algorithm developed in this study can determine the rate and buffer size through a balancing configuration for better quality robot data transmission in ARP architecture, influence the improvement of latency and reduce the packet loss.

DOI： 10.57417/jaalr.3.4_209

CiNii Research

Efficacy of Local Cache for Performance Improvement of Reliable Data Transmission in Aggregated Robot Processing Architecture 査読有り国際誌

Jalil A., Kobayashi J.

International Conference on Control, Automation and Systems 2022-November 1339 - 1344 2022年01月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

This study aims to improve the performance of message data transmission in Aggregated Robot Processing (ARP) architecture where the RELIABLE option of the RELIABILITY QoS (Quality of Service) policy is applied to a ROS 2 (Robot Operating System 2) node communication. Basically, the RELIABLE option guarantees that a publisher properly send all message data to a subscriber. However, the publisher could fail to transmit some message data to the subscriber even in the RELIABLE QoS option unless the buffer size of the publisher is enough. We introduce local cache to a sensing component to alleviate the issue in the case that the sensors output the same value in a row. The experimental results showed that the local cache improved the latency and reduced the message loss in node communication.

DOI： 10.23919/ICCAS55662.2022.10003765

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85146597288&origin=inward

Experimental Analyses of an Efficient Aggregated Robot Processing with Cache-Control for Multi-Robot System（共著）査読有り国際誌

Abdul Jalil, Jun Kobayashi

Proc. of International Conference on Control, Automation and Systems 1105 - 1109 2020年10月

Preliminary Experiments of Series Elastic Actuator Prototype utilizing Mechanical Resonance（共著）査読有り国際誌

Akihiro Yoshimi, Tsuyoshi Mori, Jun Kobayashi

Proc. of International Conference on Control, Automation and Systems 2019-October 1389 - 1393 2019年10月

担当区分：責任著者記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Korea Jeju 2017年10月15日 - 2017年10月18日

This study proposes large force generation by a robotic manipulator by means of providing series elastic actuators exploiting mechanical resonance to it instead of powerful actuators. To this end, the authors designed and assembled a prototype of series elastic actuator that resonates at around 1.0 Hz on the basis of its model and identified parameters, and carried out preliminary experiments with it and a load. The prototype actuator consists of a geared DC motor with an encoder and an elastic element. The elastic element is made of two torsion springs so that it can generate torque in both directions. It was confirmed in the preliminary experiments that the prototype actuator resonated at around 0.7 Hz. In addition, in order to prove efficacy of mechanical resonance for large force generation, output torque of the prototype actuator with the elastic element and without it was estimated using their identified physical parameters and dynamics, and compared them. The estimation results showed that the prototype actuator exploiting mechanical resonance generated 2.24 times larger torque than the one without the elastic element.

DOI： 10.23919/ICCAS47443.2019.8971642

Kyutacar

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85079102022&origin=inward

Preliminary Comparative Experiments of Support Vector Machine and Neural Network for EEG-based BCI Mobile Robot Control（共著）査読有り

Yasushi Bandou, Takuya Hayakawa, Jun Kobayashi

Journal of Robotics, Networking and Artificial Life 5 ( 4 ) 269 - 272 2019年03月

担当区分：責任著者記述言語：英語掲載種別：研究論文（学術雑誌）

Here we present experimental results of Electroencephalogram (EEG)-based Brain Computer Interface (BCI) for mobile robot control by means of Support Vector Machine (SVM) and Neural Network (NN). The authors had trained NNs using EEGs collected from subjects and verified the performance as BCI; however, the results were unsatisfactory for practical use. In this study, we have used SVM with Radial Basis Function (RBF) kernel function for further improvement and compared the performance with the NNs. Consequently, the SVMs outperformed the NNs in almost all cases.

DOI： 10.2991/jrnal.k.190220.014

Scopus

その他リンク： https://www.atlantis-press.com/journals/jrnal/125905740

Preliminary Comparative Experiments of Support Vector Machine and Neural Network for EEG-based BCI Mobile Robot Control （共著）査読有り

Yasushi Bandou,Takuya Hayakawa,Jun Kobayashi

Proceedings of The 2019 International Conference on Artificial Life and Robotics 626 - 629 2019年01月

Improving EEG-based BCI Neural Networks for Mobile Robot Control by Bayesian Optimization（共著）査読有り

Takuya Hayakawa, Jun Kobayashi

Journal of Robotics, Networking and Artificial Life 5 ( 1 ) 41 - 44 2018年06月

Improving EEG-based BCI Neural Networks for Mobile Robot Control by Bayesian Optimization （共著）査読有り

Takuya Hayakawa,Jun Kobayashi

Proceedings of The 2018 International Conference on Artificial Life and Robotics 120 - 123 2018年02月

Open Eyes Influence on Electroencephalography Signals for Constructing Neural Network Classifiers as Mobile Robot Control Brain-Computer Interface （共著）査読有り

Takuya Hayakawa, Jun Kobayashi

Proc. of International Conference on Advanced Mechatronic Systems ThuM01-03 2017年12月

Current Measurement Module for Inexpensive DC Motor Torque Control System（共著）査読有り

Tsuyoshi Mori, Jun Kobayashi

Proc. of International Conference on Control, Automation and Systems 1153 - 1154 2017年10月

Preliminary Test of Affective Virtual Reality Scenes with Head Mount Display for Emotion Elicitation Experiment（共著）査読有り

Kenta Hidaka, Haoyu Qin, Jun Kobayashi

Proc. of International Conference on Control, Automation and Systems 325 - 329 2017年10月

Experiments on Classification of Electroencephalography (EEG) Signals in Imagination of Direction using Stacked Autoencoder （共著）査読有り

Kenta Tomonaga, Takuya Hayakawa, Jun Kobayashi

Journal of Robotics, Networking and Artificial Life 4 ( 2 ) 124 - 128 2017年09月

Experiments on classification of electroencephalography (EEG) signals in imagination of direction using Stacked Autoencoder（共著）査読有り

Kenta Tomonaga,Takuya Hayakawa,Jun Kobayashi

Proceedings of The 2017 International Conference on Artificial Life and Robotics 468 - 471 2017年01月

3D-printed ball with IMU for skill acquisition in juggling three balls and preliminary tests（共著）査読有り

Mizuki Segawa,Jun Kobayashi

International Conference on Information and Communication Technology Robotics (ICT-ROBOT 2016) 2016年09月

Real-time subjective emotion evaluation with Android application for development of emotion recognition（共著）査読有り

Haoyu Qin,Kenichirou Koga,Jun Kobayashi

International Conference on Information and Communication Technology Robotics (ICT-ROBOT 2016) 2016年09月

Experiments on position measurement of small drone in heterogeneous robot system（共著）査読有り

Yuta Yoshinaga,Jun Kobayashi

International Conference on Information and Communication Technology Robotics (ICT-ROBOT 2016) 2016年09月

九州工業大学システム創成情報工学科におけるPBL教育（「物作りプロジェクト」と「超PBLプロジェクト」の紹介）

小林順

設計工学 ( 公益社団法人　日本設計工学会 ) 51 ( 9 ) 620 - 625 2016年09月

Feature Extraction for Finger Motor Imagery 査読有り

Taketoshi Wataru, Maeda Makoto, Kobayashi Jun, Inoue Katsuhiro

Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications 2016 ( 0 ) 34 - 40 2016年01月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

In recent years, the studies on Brain Computer Interface (BCI) to manipulate computer using an electroencephalogram, not through devices such as keyboards and mice, have been actively conducted. The main purpose of such BCIs is to develop communication tools for handicapped users. In this paper, we investigated differences among behaviors of Bereitschaftspotential (BP) which is one of components of movement-related cortical potentials (MRCPs), during the motor imagery of simple movements and complex movements of fingers. As a result, before and after training, some changes, such as integration or deletion, have been observed in the components related to voluntary movements, such as BP, etc. In addition, the inflow and outflow of information between Fpz and Cz have been confirmed to be reversed at intervals of 0.5 sec to 1 sec before each movement onset.

DOI： 10.5687/sss.2016.34

CiNii Article

その他リンク： http://ci.nii.ac.jp/naid/130005277722

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