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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 15 Documents
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Search results for , issue "Vol 13, No 4: December 2024" : 15 Documents clear
Adjusted linear quadratic regulator-proportional-derivative control of Quanser’s three degrees of freedom helicopter based on flower pollination algorithm under external disturbances Ghiloubi, Imam Barket; Abdou, Latifa; Lahmar, Oussama
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i4.pp432-444

Abstract

External disturbances, saturation of actuator motors, and limits of certain angular movements are commonly encountered in robotic systems, particularly those involving flight, and they present the most common and influential factors affecting the stability and performance of these systems. In this paper, a hybrid controller for a three-degree-of-freedom (3-DoF) helicopter is designed and applied to this flying robot system, taking into account the previously mentioned constraints. The proposed hybrid controller integrates proportional-derivative (PD) control with an adjusted linear quadratic regulator (ALQR) using the flower pollination algorithm (FPA) optimization method. Simulation results of travel (λ), elevation (ε), and pitch (ρ) responses, as well as experimental results of elevation and travel tracking responses under external disturbances using the bench-top Quanser’s (3-DoF) helicopter, demonstrate the robustness and good performance of the controlled system using the proposed method. The effectiveness of the proposed method is compared to several methods in the literature.
A holistic approach of stability using material parameters of manipulators Mustary, Shabnom; Kashem, Mohammod Abul; Chowdhury, Mohammad Asaduzzaman; Uddin, Jia
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i4.pp380-390

Abstract

The demand for a comprehensive method to assess stability using manipulator material parameters is high. Various material parameters, such as the Young modulus, which represents stiffness, damping, and deflection, influence the material of the robot manipulator. The correlation between robot stability and these characteristics remains unclear, as prior studies have not yet examined the collective impact of these parameters on robot manipulators. This work considers two sophisticated manipulators, namely ABB and FANUC. The main objective of this research is to construct a stability model that considers the material properties of stiffness, damping, and deflection to assess the manipulator’s stability level, which may be categorized as low, medium, or high. Furthermore, the presented stability model examines and employs numerous modified and conventional formulas for material properties to determine the level of stability. The findings show that stiffness significantly influences the stability of robot manipulators, a relationship that applies to all the examined manipulators. We also emphasize that the choice of manipulator materials significantly impacts stability maintenance. These findings are expected to enhance the design and advancement of novel robot manipulators within the industry.
Fuzzy logic assessment of X-ray tube risks in robotic C-arm angiography: a failure mode and effect analysis study Firdaus, Ade; Adriansyah, Andi; Ferdana, Nanda; Suhartina, Rahmalisa; Surakusumah, Rino Ferdian; Haekal, Jakfat; Zulhamidi, Zulhamidi; Shamsudin, Abu Ubaidillah
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i4.pp506-514

Abstract

This research examines the integration of robotic C-arm technology in angiography, a critical tool for treating cardiac conditions. The robotic C-arm, which includes an X-ray tube, is essential for scanning patients during procedures. The study also investigates the associated risks, specifically in Indonesian hospitals with cardiac facilities. Angiography is used to diagnose and treat heart disease by visualizing blood vessels and facilitating catheterization procedures. However, its mobility poses hazards and can impact the process. To address potential risks, failure mode and effect analysis (FMEA) is utilized. Traditionally, risk assessment using risk priority numbers (RPN) is conducted, but these may not accurately reflect failures due to complex evaluating processes. To overcome this limitation, fuzzy logic is employed, enhancing risk assessment accuracy. Through this approach, twenty-seven failure modes are identified across two brands, with ten major ones prioritized using fuzzy logic. These findings facilitate the development of preventive measures to mitigate future failures and enhance patient safety during angiography in hospitals. In conclusion, the study underscores the importance of robust risk management in medical equipment, particularly in dynamic environments. By integrating fuzzy logic into risk assessment, the study improves prioritization accuracy, enabling effective allocation of resources for preventive actions.
Design and implementation of deep neural network hardware chip and its performance analysis Pant, Aruna; Kumar, Adesh
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i4.pp485-494

Abstract

The artificial neural network (ANN) with a single layer has a limited capacity to process data. Multiple neurons are connected in the human brain, and the actual capacity of the brain lies in the interconnectedness of multiple neurons. As a specified generalization of ANN deep learning makes use of two or more hidden layers, which implies that a greater number of neurons are required to construct the model. A network that has more than one hidden layer, also known as two or more hidden layers, is referred to as a deep neural network, and the process of training such networks is referred to as deep learning. The research article focuses on the design of a multilayer or deep neural network presented for the target field programmable gate array (FPGA) device spartan-6 (xc6stx4-2t9g144) FPGA. The simulation is carried out using Xilinx ISE and ModelSim software. There are two hidden layers in which (2×1) multiplexer blocks are utilized for processing twenty neurons into the output of ten neurons in the first hidden layer and demultiplexers (1×2) and vice versa. The hardware utilization is estimated on FPGA to compute the performance of the deep neural hardware chip based on memory, flip flops, delay, and frequency parameters. The design is scalable and applicable to various FPGA devices, which makes the work novel. FPGA-based neuromorphic hardware acceleration platform with high speed and low power for discrete spike processing on hardware with great real-time performance.
Theoretical and experimental analysis of unbalanced doubly fed induction generators Diboune, Yaakoub; Hachelaf, Redouane; Kouchih, Djilali
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i4.pp476-484

Abstract

In this paper, a novel approach has been developed for the modeling and analysis of doubly fed induction generators operating under unbalanced load conditions. This comprehensive approach considers the derivation of the doubly fed induction generator’s neutral voltage during unbalanced conditions. Using this innovative approach, important and extremely precise signatures on stator currents and voltages have been extracted during a rational simulation time. It has been shown that for unbalanced conditions, an abnormal operation is produced. It is characterized by unbalanced stator voltages, currents, and specific harmonics through the stator variables. These harmonics have been proposed to detect unbalanced conditions. The consistency and reliability of this approach for the analysis and modeling of unbalanced doubly fed induction generators are validated by the coherence and good correlation between experimental and simulation results.
An introduction to using QR codes in web portals for synchronizing calendar events over phones Sethi, Inder Pal Singh; Gupta, Om Pradyumana; Bhaisare, Sulbha; Dwivedi, Ritesh Kumar; Kapoor, Misha
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i4.pp469-475

Abstract

An optical label with machine-readable information about the object it is attached to is called a quick response (QR) code. QR codes frequently hold information for a tracker, locator, or identifier that directs users to a website or application. To efficiently store data, a QR code has four standardized encoding modes: kanji, byte or binary, alphanumeric, and numeric. As a means of identifying a wide range of commercial goods, including transactions, ads, and other public notices, the QR code gained popularity. In our web portal, the proposed QR code model synchronizes all the event details synchronously in the mobile calendar. QR code is used for web-to-mobile data transfer, saving events or meeting details in the mobile calendar. Anyone with a smartphone can view the data encoded in a QR code by scanning it. Although it makes it easier for end users to decode QR codes, verifying access to the encoded data is a cause for worry. Our proposed model validates access to data through the QR code, allowing only authorized personnel to access data. To ensure accessibility control, the proposed model has the functionality of a one-time password (OTP) that enhances application security. The model achieved an average decoding speed of 157 milliseconds with an error rate of 0.38%.
Integrating artificial immune systems and multi-layer perceptron-biogeography-based optimization for enhanced inverse kinematics in robotic arm Serat, Amel; Djebbar, Bachir
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i4.pp401-409

Abstract

Determining required joint angles to achieve a desired position in a manipulator’s arm is a complicated problem without simple analytical solutions. This paper researches several computational methods based on artificial intelligence (AI) for calculating the joint positions of the 6-DOF robotic arm. We can extrapolate relevance, for example, to the crucial role that robotic manipulator arms play in industrial and medical applications, where enhanced precision and movement efficiency may sharply boost performance and expand applicability. Here, we investigate the effectiveness of methods, such as the artificial immune system (AIS) and multi-layer perceptron-biogeography-based optimization (MLP-BBO). Those AI-driven methods have been applied to determine joint angles for reaching desired positions through simulations for the robotic arm. The results show that the AIS and MLP-BBO approach can handle the intrinsic complexities of the task, thus testifying to the practicability and dependability of these two methods in this application. From the findings in the study, it was indicated that AI-driven techniques can effectively answer the complex problem of the robotic manipulator arm in finding joint angles.
Low-cost multi-sensing fire-fighting robot with obstacle avoidance mechanism Oyelami, Adekunle Taofeek; Oyadokun, Joshua Ayomide; Akintunlaji, Olusola A.; Ihenacho, George C.
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i4.pp373-379

Abstract

Robots are mostly optimized for tasks that require strength exceeding that of humans or for operations in hazardous environments. The fire-fighting robot developed has multiple sensing capabilities with obstacle avoidance mechanisms and is divided into two units: the robot and the static unit. The robot is equipped with three flame sensors to detect flames (infrared radiation) in three directions, an ultrasonic sensor to avoid obstacles, a wireless receiver to receive data from the static unit, a magnetometer giving the robot a sense of direction, and a unit of Arduino Mega microcontroller serving as the central controlling platform. The static unit has four flame sensors and a transmitter that transmits signals to the robot unit, which an Arduino Uno directly controls. A prototype was developed, which helps prevent the escalation of fires in the home as it can detect, navigate and extinguish flames while avoiding obstacles autonomously.
The future of artificial intelligence-driven robotics: applications and implications Sutikno, Tole
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i4.pp361-372

Abstract

Artificial intelligence (AI)-driven robotics is a rapidly evolving field that is transforming various industries, including healthcare, manufacturing, transportation, logistics, security, retail, agri-food, and construction. The integration of artificial intelligence algorithms and machine learning techniques has propelled robotics beyond mere automation, enabling machines to modify, alter, adjust, learn, and interact with the world in ways previously deemed science fiction. The relentless pursuit of creating intelligent robotic systems has led to a symbiotic relationship between human inventiveness and AI, with AI-driven autonomous cars, drones, and robots transforming transportation, healthcare, and exploration. It offers flexibility and learning capabilities, transforming the way machines interact with humans. The integration of AI and robotics marks a transformative era in which machines become companions and cognitive extensions of human capabilities. In the future, we expect AI-driven robotics to bring significant changes to employment and societal well-being. However, the development of AI-driven robotics, which is the integration of AI and robotics, faces numerous challenges, including ethical concerns, legal issues, regulations, societal implications, and job market impacts for the proliferation of intelligent machines. Furthermore, it also presents challenges in terms of technical complexities in its development.
Vision-based approach for human motion detection and smart appliance control Swami, Siddharth; Singh, Rajesh; Gehlot, Anita; Iqbal, Mohammed Ismail; Sharma, Sameer Dev; Kumar, Dharmendra; Shah, Sanjeev Kumar
IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v13i4.pp445-451

Abstract

This study focuses on the use of computer vision technology and motion detection sensors to create an intelligent system that recognizes human presence in monitored spaces. The system uses a relay module for automation and control of household appliances while sensing motion detection, operated by an ESP32 microcontroller. This innovative solution addresses two major issues in home automation: reliable human presence recognition and seamless appliance control. The research merges a camera-based vision system with motion sensors, comparing motion and vision-based identification. The ESP32 microcontroller improves motion detection precision and context awareness by integrating motion sensors and computer vision technologies. The integration of a camera module allows real-time analysis and recognition of human presence, reducing false alarms. The relay module also enables automated control of home appliances, synchronizing and feedbacking operations with sensed human presence. The dynamic adaptation of the system improves user convenience and energy efficiency.

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