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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Robotics and Control (JRC) Indonesian Journal of Electrical Engineering and Computer Science
Minoru Sasaki
Gifu University
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mechanical Engineering

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Combination of Flex Sensor and Electromyography for Hybrid Control Robot Muhammad Ilhamdi Rusydi; Muhammad Ismail Opera; Andrivo Rusydi; Minoru Sasaki
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 5: October 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i5.7028

Abstract

The alternative control methods of robot are very important to solved problems for people with special needs. In this research, a robot arm from the elbow to hand is designed based on human right arm. This robot robot is controlled by human left arm. The positions of flex sensors are studied to recognize the flexion-extension elbow, supination-pronation forearm, flexion-extension wrist and radial-ulnar wrist.The hand of robot has two function grasping and realeasing object. This robot has four joints and six flex sensors are attached to human left arm. Electromyography signals from face muscle contraction are used to classify grasping and releasing hand. The results show that the flex sensor accuracy is 3.54° with standard error is approximately 0.040 V. Seven operators completely tasks to take and release objects at three different locations: perpendicular to the robot, left-front and right-front of the robot. The average times to finish each task are 15.7 ssecond, 17.6 second and 17.1 second. This robot control system works in a real time function. This control method can substitute the right hand function to do taking and releasing object tasks.
Autonomous Movement Control of Coaxial Mobile Robot based on Aspect Ratio of Human Face for Public Relation Activity Using Stereo Thermal Camera Muhammad Ilhamdi Rusydi; Aulia Novira; Takayuki Nakagome; Joseph Muguro; Rio Nakajima; Waweru Njeri; Kojiro Matsushita; Minoru Sasaki
Journal of Robotics and Control (JRC) Vol 3, No 3 (2022): May
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i3.14750

Abstract

In recent years, robots that recognize people around them and provide guidance, information, and monitoring have been attracting attention. The mainstream of conventional human recognition technology is the method using a camera or laser range finder. However, it is difficult to recognize with a camera due to fluctuations in lighting 1), and it is often affected by the recognition environment such as misrecognition 2) with a person's leg and a chair's leg with a laser range finder. Therefore, we propose a human recognition method using a thermal camera that can visualize human heat. This study aims to realize human-following autonomous movement based on human recognition. In addition, the distance from the robot to the person is measured with a stereo thermal camera that uses two thermal cameras. A coaxial two-wheeled robot that is compact and capable of super-credit turning is used as a mobile robot. Finally, we conduct an autonomous movement experiment of a coaxial mobile robot based on human recognition by combining these. We performed human-following experiments on a coaxial two-wheeled robot based on human recognition using a stereo thermal camera and confirmed that it moves appropriately to the location where the recognized person is in multiple use cases (scenarios). However, the accuracy of distance measurement by stereo vision is inferior to that of laser measurement. It is necessary to improve it in the case of movement that requires more accuracy.
Pattern Recognition of Overhead Forehand and Backhand in Badminton Based on the Sign of Local Euler Angle Muhammad Ilhamdi Rusydi; Syamsul Huda; Febdian Rusydi; Muhammad Hadi Sucipto; Minoru Sasaki
Indonesian Journal of Electrical Engineering and Computer Science Vol 2, No 3: June 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v2.i3.pp625-635

Abstract

Studying the badminton skill based on the arm movement is a challenge since the limitation of the sensor such as camera to record the movement parameter. This study proposed a new method to determine the pattern of arm movement for forehand and backhand strokes in badminton based on the sign of the local Euler angle gradient from four points of right arm segments. Each segment was identified by motion sensor attached to the dorsal surface of the hand (sensor 1), wrist (sensor 2), elbow (sensor 3) and shoulder (sensor 4). Three certified coaches participated in this research to determine the arm movement patterns for forehand and backhand strokes. Skills in forehand and backhand strokes from eight professional players and eight amateur players were observed to determine the pattern. The result showed that the local Euler angle can be used to recognize the arm movement pattern. Based on the observed patterns, the professional players had a higher similarity to the coaches’ patterns than those amateur players to the coaches’.
A Systematic Literature Review of Automation Quality of Service in Computer Networks: Research Trends, Datasets, and Methods Budi Sunaryo; Muhammad Ilhamdi Rusydi; Ariadi Hazmi; Minoru Sasaki
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 2 (2023): April 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i2.4810

Abstract

The article is a systematic literature review of the use of automation for quality of service (QoS) in computer networks. It summarizes the research trends, datasets, and methods used in the field and provides an overview of the current state of the art. The focus of the review is on the use of automation for QoS management and improvement in computer networks, including the use of machine learning, artificial intelligence, and other computational techniques. The review highlights the need for further research and development in this area and provides insights into future directions for the field. The review covered a wide range of studies, including research papers and conference proceedings, and involved a comprehensive database search of the Scopus database covering journals and proceedings such as the Institute of Electrical and Electronics Engineers (IEEE) Xplore, Association for Computing Machinery (ACM) Digital Library, Springer, and ScienceDirect databases between 2017 and September 2022. From these databases, 1856 metadata were found, which eventually became seventy-three metadata after going through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol.
Co-Authors Andrivo Rusydi Ariadi Hazmi Aulia Novira Budi Sunaryo Febdian Rusydi Joseph Muguro Kojiro Matsushita Muhammad Hadi Sucipto Muhammad Ismail Opera Rio Nakajima Rusydi, Muhammad Ilhamdi Syamsul Huda Takayuki Nakagome Titus Mulembo Toshiharu Yasui Waweru Njeri