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IAES International Journal of Robotics and Automation (IJRA)
Published by Institute of Advanced Engineering and Science
ISSN : 20894856     EISSN : 27222586     DOI : -
Core Subject : Engineering,
Automotive Engineering Electrical & Electronics Engineering
Robots are becoming part of people's everyday social lives and will increasingly become so. In future years, robots may become caretaker assistants for the elderly, or academic tutors for our children, or medical assistants, day care assistants, or psychological counselors. Robots may become our co-workers in factories and offices, or maids in our homes. The IAES International Journal of Robotics and Automation (IJRA) is providing a platform to researchers, scientists, engineers and practitioners throughout the world to publish the latest achievement, future challenges and exciting applications of intelligent and autonomous robots. IJRA is aiming to push the frontier of robotics into a new dimension, in which motion and intelligence play equally important roles. Its scope includes (but not limited) to the following: automation control, automation engineering, autonomous robots, biotechnology and robotics, emergence of the thinking machine, forward kinematics, household robots and automation, inverse kinematics, Jacobian and singularities, methods for teaching robots, nanotechnology and robotics (nanobots), orientation matrices, robot controller, robot structure and workspace, robotic and automation software development, robotic exploration, robotic surgery, robotic surgical procedures, robotic welding, robotics applications, robotics programming, robotics technologies, robots society and ethics, software and hardware designing for robots, spatial transformations, trajectory generation, unmanned (robotic) vehicles, etc.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 7 Documents
 1 
Search results for , issue "Vol 11, No 1: March 2022" : 7 Documents clear
An alternative technique to reduce time, cost and human effort during natural or manufactured disasters Samaher Al-Janabi; Ayad Alkaim; Ahmed Rahem
IAES International Journal of Robotics and Automation (IJRA) Vol 11, No 1: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v11i1.pp10-20

Abstract

The world suffers from a very large number of missing persons, ranging from about 250,000 to about one million people for various reasons in recent years. Therefore, the process of finding and tracing the missing persons as a result of a plane crash, fire or explosion in a particular area is a humanitarian and religious and national duty, and is one of the most important issues in our country. So, the idea of using a drone to find missing people was invested. We have designed system that collects real-time data and analyzes in a smart way and utilizes global positioning system (GPS) to locate people and track their impact. The idea of this work has been developed and implemented. They represent it in the form of a triangular problem, which included: First, how to locate the missing persons and send video broadcasts to a calculator or mobile device remotely. Analyze the data collected in real time, and send a report identifying the safe path that can be taken to reach the missing persons. The second stage is collection the data in the master computer and analysis it, while the final stage determines the coordinates of the location to the missing persons and the best possible way to reach of them.
A smart door prototype with a face recognition capability Ivan Surya Hutomo; Handy Wicaksono
IAES International Journal of Robotics and Automation (IJRA) Vol 11, No 1: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v11i1.pp1-9

Abstract

This research aimed to integrate a face recognition capability in a smart door prototype. By using a camera-based face recognition, the house owner does not need to make physical contact to open the door. Avoid physical contact is important due to the coronavirus disease 2019 (COVID19) pandemic. Raspberry Pi 3B was used as the main controller, while a servo motor was utilized as a locking door actuator. The program was developed using Node-RED, Blynk, and message queue telemetry transport (MQTT) platforms which are very powerful for developing internet of things (IoT) devices. All of the programs were coded using Python. Haar cascade and local binary pattern histogram methods were implemented on the face recognition stage. Google Assistant integration was done by using Dialogflow and Firebase as Google Cloud services. Integration of face recognition and the smart door was successful. The smart door was unlocked if faces were recognized (average threshold=60%). If a face was not recognized, an email notification containing a face image is sent to the house owner. The Google Assistant could handle user requests successfully with a success rate of 92.8% from 147 trials.
Recognizing facial emotions for educational learning settings Akputu Oryina Kingsley; Udoinyang G. Inyang; Ortil Msugh; Fiza T. Mughal; Abel Usoro
IAES International Journal of Robotics and Automation (IJRA) Vol 11, No 1: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v11i1.pp21-32

Abstract

Educational learning settings exploit cognitive factors as ultimate feedback to enhance personalization in teaching and learning. But besides cognition, the emotions of the learner which reflect the affective learning dimension also play an important role in the learning process. The emotions can be recognized by tracking explicit behaviors of the learner like facial or vocal expressions. Despite reasonable efforts to recognize emotions, the research community is currently constraints by two issues, namely: i) the lack of efficient feature descriptors to accurately represent and prospectively recognize (detecting) the emotions of the learner; ii) lack of contextual datasets to benchmark performances of emotion recognizers in the learning-specific scenarios, resulting in poor generalizations. This paper presents a facial emotion recognition technique (FERT). The FERT is realized through results of preliminary analysis across various facial feature descriptors. Emotions are classified using the multiple kernel learning (MKL) method which reportedly possesses good merits. A contextually relevant simulated learning emotion (SLE) dataset is introduced to validate the FERT scheme. Recognition performance of the FERT scheme generalizes to 90.3% on the SLE dataset. On more popular but noncontextually datasets, the scheme achieved 90.0% and 82.8% respectively extended Cohn Kanade (CK+) and acted facial expressions in the wild (AFEW) datasets. A test for the null hypothesis that there is no significant difference in the performances accuracies of the descriptors rather proved otherwise (χ2=14.619,df=5,p=0.01212) for a model considered at a 95% confidence interval.
Active object search using a pyramid approach to determine the next-best-view Karen-Lizbeth Flores-Rodriguez; Felipe Trujillo-Romero; Jose-Joel Gonzalez-Barbosa
IAES International Journal of Robotics and Automation (IJRA) Vol 11, No 1: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v11i1.pp70-88

Abstract

The development of service robotics continues to arouse interest in the scientific community due to the complexity of the activities performed like interaction in human environments, identifying and manipulating objects, and even learning by themselves. This paper proposed to improve the perception of the environment by searching for objects in service robotics tasks. We present the development and implementation of an active object search method based on three main phases: Firstly, image pyramid segmentation to examine in detail the im- age features. Second step, object detection at each level of the pyramid through a local feature descriptor and a mutual information calculation. Finally, the next camera position selection through analyzing the object detections accumulation in the pyramid. To evaluate the implementation of the proposed method, we use a NAO robot in a familiar place for humans, such as an office or a home. Ordinary objects are part of our database with the premise that a robot must know them before looking for an object. The results in the experiments showed an acceptable performance in simulation and with a real platform.
An effective approach to enhance the balancing control in bycycorobot using the soft computing techniques Aswant Kumar Sharma; Dhanesh Kumar Sambariya
IAES International Journal of Robotics and Automation (IJRA) Vol 11, No 1: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v11i1.pp43-61

Abstract

The balancing and control of bycycorobot is a challenging task. The pre-specified controller available in the literature for balancing has been reduced with novel optimization to improve the effectiveness of balancing, uncertainty, and the complexity of the complete system. The novel Harris hawk optimization (HHO) which is based on the hunting behavior of the hawk has been utilized to improve the balancing of the bycycorobot. The paper proposes the decreased order controller of a pre-specified controller for a bycycorobot. The obtained controller response with bycycorobot in the complete closed loop is analyzed, and the best performance is compared with the reduced order controller available in the literature. The comparison is based on the response indices and response characteristics.
The surface electromyography noise filtering and unwanted recordings attenuation for lower limb robotic system Abdelhakim Deboucha
IAES International Journal of Robotics and Automation (IJRA) Vol 11, No 1: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v11i1.pp62-69

Abstract

Exoskeleton robotic device (ERD) for rehabilitation purposes, physically interacts alongside with the user where high cognitive interaction and the safe human - machine system is required. To ensure safe interaction, there is a need to detect the user’s motion intention. One of the bio-signals that have been found to reflect directly the individual’s motion intention is surface electromyography (sEMG). However, sEMG signals are inevitably full of noises, not to mention the unwanted recordings and other artifact s between muscles where they cannot be freely used as a control signal for ERD. This paper presents the use of the Butterworth filter for noise suppression and the attenuation of unwanted recordings. Using classical Butterworth filter typically is unable to eliminate or attenuate the unwanted contamination on the signal of interest to its baseline level. Therefore, it is critical to modify the Butterworth filter at this stage. sEMG signals from the biceps femoris and rectus femoris muscles of seven health y male young adults were recorded in this study. The onset/ offset technique is utilized to detect the presence of the additional signal contaminated on the signal of interest. If the onset/offset index points are not approximately correlated with the movement, this means there is a contaminated measurement on the signal of interest. At this interval, a filter with distributed cutoff frequency plays the role to have the already smoothed baseline signal. In summary, the modified Butterworth filter shows to have a good performance to suppress the noises and to attenuate the unwanted recordings adaptively which ensures a safe human-machine system.
Person following control for a mobile robot based on color invariance corresponding to varying illumination Shinsuke Oh-hara; Kaoru Saito; Atsushi Fujimori
IAES International Journal of Robotics and Automation (IJRA) Vol 11, No 1: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v11i1.pp33-42

Abstract

In this paper, we present a method of person following control for a mobile robot using visual information. Color information is often used for object tracking. Color information of objects varies greatly under illumination changing environment. In such conditions, the robot controlled by visual information may lose sight of a person. In this paper, we consider a robust person following method by color invariance and image-based control. Color invariance shows robust features of colored objects in terms of changing illumination conditions. At first, we estimate the lowest positions of both feet of a tracked person through particle filters based on color invariances. Then, we control the velocity of the robot to track the person by using the image-based controller. Experimental results using an actual robot demonstrate the effectiveness of the proposed method.

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