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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 9 Documents
 1 
Search results for , issue "Vol 12, No 4: December 2023" : 9 Documents clear
Robotic inspection and automated analysis system for advanced manufacturing Maged Mikhail; Karen Abed
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i4.pp352-364

Abstract

Companies have developed various systems to improve their processes. These processes’ focus has been to produce more quantity in less time. To accomplish this task, it is important to also consider defects. Defective products can cause delays in the production line, rework, and the loss of money, time, and resources. This project focused on developing an integrated inspection system. Previous research has been done regarding types of vision systems, in-line inspections, and feedback data collection. A programmable logic controller (PLC) was used to control when the conveyor belt starts and stops. When the object has reached a certain position, the camera detects if the object passed or failed the process. If the object fails, the robot will pick up the bottle and take it out of the line. Human-machine interface (HMI) was also integrated, which shows how many bottles have passed and failed with a light that will indicate if a certain object has passed or failed. Feedback from the inspection process can help solve potential issues from different machines and processes. The testbed was designed, integrated, and tested in the paper to perform a feedback analysis for the production line. The setup consisted of MicroLogix PLC, Fanuc robot LR Mate 200iD and Cognex camera.
Object distance estimation using a monovision camera Efemenah Endurance Idohen; Olatunde Mathew Afolayan; Umar Ali Umar
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i4.pp325-331

Abstract

In computer vision, most monovision cameras used for estimating the position of an object only estimate the 2D information of the object without the depth information. Estimating the depth information, which is the distance between the target object and the camera is quite challenging but, in this paper, a less computationally intensive method was used to estimate the object’s distance to complete the 3D information needed to determine the object’s location in cartesian space. In this method, the object was positioned in front of the camera at a sequential distance and was measured directly. The distances measured in the experiment with a set of training data obtained from the image were fitted into a curve using the least-square framework to derive a non-linear function that was used for estimating the object’s distance also known as the z-coordinate. The result from the experiment showed that there was an average error of 1.33 mm between the actual distance and the estimated distance of the object. Hence, this method can be applied in many robotic and autonomous systems applications.
Construction of automated optimal control systems with elements of artificial intelligence Khu Ven Tsen; Zhanat Umarova; Pernekul Kozhabekova; Nabat Suieuova
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i4.pp365-372

Abstract

This article examines the widespread introduction of artificial intelligence technologies, means of their implementation and support as a determining factor in the development of scientific and technological progress. On this basis, various advanced objects of various functional purposes are created, which are characterized as “smart”. Their distinguishing feature is the ability to implement a “reasonable” way of functioning, taking into account the prevailing circumstances. This ability is expressed in the fact that in the object automatically, i.e., without human participation, or with minimal human participation, the most rational or optimal modes of functioning are supported, the definition of which involves the performance of operations containing signs of rational activity. This “smart” behavior of technical objects is mainly determined by the “intelligent” functioning of the control systems built into them. In particular, intelligent automated systems for optimal control. In accordance with this, the development of new approaches and methods that expand the possibilities of building such control systems should be considered as an urgent and priority task.
Traffic lights time strategy for T-junctions of toll road gate Tomi Tristono; Setiyo Daru Cahyono; Seno Aji; Pradityo Utomo; Joko Triono
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i4.pp373-382

Abstract

Vehicles wishing to pass on the toll road must diverge from the traffic flow on public roads. The toll road movement consists of low vehicles (LV) and heavy vehicles (HV). The public road movement is a mixed traffic flow consisting of LV, HV, motorcycles, and unmotorized vehicles. Traffic lights are used at the T-junction of the toll road gate for travel safety management. The traffic lights that implement a fixed-time strategy should be optimized for efficiency. This study aims to review the safety of travel management at T-junctions for the toll road gate when adaptive traffic lights are used. The structural complexity of mathematical modeling with Petri net is used to analyze and measure the feasibility study. Results illustrate that the structural complexity of the traffic lights that implement a fixed time strategy equals 0.387. It is equal to 0.489 for the adaptive traffic lights. The structural complexity of adaptive traffic lights is 25% higher than conventional systems that implement a fixed-time strategy. The adaptive traffic lights time strategy is feasible for travel safety for road users. The travel time is efficient and comfortable because the delay is low. Furthermore, traffic lights can adjust to the demand of vehicles queuing.
An emotion recognition system: bridging the gap between humans-machines interaction Ahmed Nouman; Hashim Iqbal; Muhammad Khurram Saleem
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i4.pp315-324

Abstract

Human emotion recognition has emerged as a vital research area in recent years due to its widespread applications in psychology, healthcare, education, entertainment, and human-robot interaction. This research article comprehensively analyzes a machine learning-based six-emotion classification algorithm, focusing on its development, evaluation, and potential applications. The study aims to assess the algorithm's performance, identify its limitations, and discuss the importance of selecting appropriate image descriptors for accurate emotion classification. The algorithm achieved an overall accuracy of 92.23\%, showcasing its potential in various fields. However, the classification of specific emotions, particularly ``excited'' and ``afraid'', demonstrated some limitations, suggesting further refinement. The study also highlights the significance of choosing suitable image descriptors, with the manual distance calculation used in the framework proving effective. This article offers insights into developing and evaluating a six-emotion classification algorithm using a machine learning framework, emphasizing its strengths, limitations, and possible applications in multiple domains. The findings contribute to ongoing efforts in creating robust, accurate, and versatile emotion recognition systems that cater to the diverse needs of various applications across psychology, healthcare, robotics, education, and entertainment.
The use of artificial intelligence in interrogation: lies and truth Yi-Chang Wu; Yao-Cheng Liu; Ru-Yi Huang
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i4.pp332-340

Abstract

Following the development of artificial intelligence technology, a new trend has emerged in which this technology is increasingly used in case investigations. In this study, we developed a lie detection system that can instantly determine whether an interrogee is lying depending on their emotional responses to specific questions. Investigators then use these data, in addition to their personal experiences and case information, to adjust their interrogation strategies and techniques, thereby leading the interrogee to confess and accelerating the investigation process. Our system collects data using OpenFace and performs deep learning using gcForest. Deep learning training was performed using a real-life trial dataset, the Miami University Deception Detection Database, and a bag-of-lies dataset, and their corresponding trained systems achieved a detection accuracy of 95.11%, 90.83%, and 88.19%, respectively.
4-degree-of-freedom voice-controlled robotic arm Adekunle Taofeek Oyelami; Wahab Fisayo Elegbeji; Oluwabukunmi Adeniyi
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i4.pp341-351

Abstract

People with impairments who utilize robotic arms have a great deal more independence in their daily lives. The robotic arm can help persons with specific needs by using voice control, which is practical. The working mechanism is fashioned to have four degrees of freedom (4-DOF) with the inclusion of a jaw or gripper. The Arduino microcontroller, the speech module, and the arm are the main components of the robotic arm, which is a lightweight model driven by four motors. The servo motor is used to supply the rotational motion in the arm’s three rotary joints and end effector. Rotation in two directions is made possible by the geared DC motors employed, which alter their direction of rotation if the polarity is flipped. The automatic voice recognition technology aids in comprehending spoken words picked up by a microphone. The HM2007 processor, the brains of the speech recognizer, is necessary for the speech recognizer to function. Digital commands are created from analog speech input. These commands are used as input to the Arduino thereby resulting in a system whereby the human voice gives a continuous control signal to operate a real and functional robotic arm.
In-car speech enhancement based on source separation technique Jeyasingh Pathrose; Mohamed Ismail
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i4.pp383-393

Abstract

This work addresses the solution of localizing and enhancing hands-free speech inside the car environment. Cars have different types of sounds from outside, co-passengers dialogue and noise. To provide better-quality speech, a microphone array-based beamforming technique is used. This research work proposes the method for selected source localization, source separation, and enhancement. An estimation of the direction of arrival (DOA) to localize the signal direction and preferred direction is selected for speech enhancement. The spiral and sine-cosine algorithm (SSCA) algorithm is combined with an adaptive least mean square to adapt the system for different environments. The algorithm is implemented in hardware and tested in a real-time car environment. The results showed significant improvement in signal-to-noise ratio (SNR) of 5.2 dB and perceptual evaluation of speech quality (PESQ) of 2.3. Finally, the model is fine-tuned for the car to get better quality. The proposed technique is efficient, and results are compared with existing methods.
DEMAP: differential evolution mapping for network on chip optimization Maamar Bougherara; Rafik Amara; Rebiha Kemcha
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i4.pp394-404

Abstract

Network-on-chip (NoC) is a new paradigm for system-on-chip (SoC) design, which facilitates the interconnection and integration of complex components. Since this technology is still new, significant research efforts are needed to accelerate and simplify the design phases. Mapping is a critical phase in the NoC design process, as a mismatch of application software components can significantly impact the final system's performance. Therefore, it is essential to develop automated tools and methods to ensure this step. The main objective of this project is to develop a new approach that can be used to map applications on the NoC architecture to reduce communication costs. To achieve this goal, we have opted for an optimization algorithm, specifically the differential evolution algorithm.

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