IAES International Journal of Robotics and Automation (IJRA)
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.
Articles
470 Documents
<![CDATA[Evaluating the development and cutting capacity of a one-square computer numeric controlled milling machine ]]>
<![CDATA[Ajayi, Oluwaseun Kayode]]>;
<![CDATA[Oyeniran, Ayodele Temitope]]>;
<![CDATA[Du, Shengzhi]]>;
<![CDATA[Malomo, Babafemi Olamide]]>;
<![CDATA[Alao, Kolawole Oluwaseun]]>;
<![CDATA[Omotosho, Quadri Ayomide]]>;
<![CDATA[Fawole, Marvellous Oluwadamilare]]>;
<![CDATA[Lasaki, Ayomide Isaiah]]>;
<![CDATA[Thompson, Godwin]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 14, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v14i3.pp451-462
<![CDATA[Traditional subtractive technology is rapidly losing significance with the advent of digital manufacturing technologies, which offer affordable machining with high accuracy and repeatability. Computer numeric controlled (CNC) machining has been around for a while; however, it has been costly to own one. Since the concept of CNC machining is now broadly understood and open-source software is available for control, designers can make use of available local materials to develop cheaper CNC machines. Hence, this presents the evaluation of the design and development of a one-square-meter CNC milling machine. The control was implemented on Arduino Uno, while open-source Universal G-code Sender (UGS) and G-code reference block library (GRBL) were used for the G-code generation and machine control, respectively. The built CNC was calibrated and tested on wood and plastic materials, and the resulting products were acceptable in accuracy up to ±0.02 mm in the first trial, but attained perfect accuracy by the third trial. Multiple tests repeatedly showed that accuracy was maintained. Since the machine is reconfigurable, future work entails automation and incorporating laser cutting capabilities into the machine.]]>
<![CDATA[River cleaning robot using Arduino microcontroller ]]>
<![CDATA[Ramadevi, Dubala]]>;
<![CDATA[Chenchireddy, Kalagotla]]>;
<![CDATA[Rekha, Barkam]]>;
<![CDATA[Prathyusha, Sunkari]]>;
<![CDATA[Shravani, Koriginja]]>;
<![CDATA[Bhargavi, Karnati]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 14, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v14i3.pp332-338
<![CDATA[River cleaning robots represent a promising technological solution to address the pervasive issue of water pollution in river systems. These autonomous devices are designed to collect and remove various types of debris from river environments, contributing to improved water quality and ecosystem health. This abstract summarizes the key aspects of river cleaning robots, including their technological advancements, operational mechanisms, and environmental impact. River cleaning robots have evolved significantly from early mechanical designs to sophisticated autonomous systems. Initially, these robots were equipped with basic skimming and collection mechanisms. Recent advancements have incorporated state-of-the-art technologies, including artificial intelligence, machine learning, and advanced sensor systems. Modern river cleaning robots can autonomously navigate complex river environments, detect and classify different types of debris, and operate efficiently with minimal human intervention. The operational capabilities of these robots are enhanced by various design features such as mobility systems, debris collection mechanisms, and renewable power sources. Mobility systems allow robots to maneuver through diverse water conditions, while collection mechanisms like nets, scoops, and suction devices enable effective debris removal. Many robots are powered by renewable energy sources, such as solar panels, which contribute to their sustainability and reduce their environmental footprint.]]>
<![CDATA[Internet of Things-enabled smart robotic baggage monitoring and tracking system for enhanced traveler convenience and security ]]>
<![CDATA[Gehlot, Anita]]>;
<![CDATA[Singh, Rajesh]]>;
<![CDATA[Mahala, Rahul]]>;
<![CDATA[Singh, Vivek Kumar]]>;
<![CDATA[Gupta, Mahim Raj]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 14, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v14i2.pp290-300
<![CDATA[Baggage travel is a significant issue, causing inconveniences and financial losses for travellers. The rise in efficient international and domestic travel has led to the need for live baggage tracking systems. Traditional methods, such as manual tracking and locks, are inefficient and counterproductive due to power limitations. IoT has revolutionized baggage management by providing real-time tracking feedback and enhancing security. IoT-enhanced smart luggage systems use biometric locks, GPS tracking, and smart locking mechanisms to prevent theft and unauthorized usage. Geofencing allows users to draw boundaries for luggage, and smart luggage systems can adapt to airport security requirements. Some smart suitcases also have self-following features, allowing travellers to have better control over their bags. IoT-enabled baggage solutions also improve airport and travel centre efficiency. RFID and barcode identification devices enable airline employees to quickly recognize, monitor, and manage luggage, reducing waiting times and loss risks. Cloud-based systems allow users to remember their luggage and receive travel suggestions based on predicted frequency of use. IoT-enabled baggage management systems have the potential to transform airport ecosystems into smarter ones through automated tracking with minimal human involvement and errors. AI and machine learning can also proactively address concerns and improve the overall customer journey.]]>
<![CDATA[Design and implementation of QUADRESCUE: A ROS-based quadruped robot for disaster response support ]]>
<![CDATA[Deshmukh, Sanjay]]>;
<![CDATA[Chanakya, Ojas]]>;
<![CDATA[Gabani, Om]]>;
<![CDATA[Patni, Kashish]]>;
<![CDATA[Deshmukh, Asmita]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 14, No 3: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v14i3.pp387-398
<![CDATA[Search and rescue (SAR) operations in hazardous environments demand robotic systems capable of traversing complex terrains while ensuring responder safety. Traditional wheeled platforms often fail in debris-laden areas, and fully autonomous quadrupeds remain financially out of reach for many rescue agencies. This paper presents the design and development of QUADRESCUE, a modular operator-assisted quadruped robot built to bridge the gap between affordability and capability in disaster response. QUADRESCUE delivers core SAR functionalities including remote visual inspection, real-time terrain mapping via an RGB-D camera, payload transport, and GPS-based survivor localization. Built with a robust three degrees of freedom (3DoF) per leg design, the robot uses inverse kinematics algorithms to precisely control twelve servo motors for stable locomotion across uneven terrain. The system integrates the robot operating system (ROS) for seamless operation, real-time joystick control for easy navigation, an IMU for orientation sensing, and a GPS module with 3-meter accuracy. Field evaluations demonstrate 80–94% success rates on challenging surfaces, substantially outperforming wheeled counterparts 19% to 39% with a 200-meter control range and 45 minutes of runtime. QUADRESCUE offers a lightweight, cost-effective, and repairable solution that combines practical usability with advanced performance, making it well-suited for real-world deployment in emergency rescue situations.]]>
<![CDATA[A method integral sliding mode control to minimize chattering in sliding mode control of robot manipulator ]]>
<![CDATA[Nguyen, Mai Hoang]]>;
<![CDATA[Nguyen, Truc Thi Kim]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 14, No 3: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v14i3.pp345-355
<![CDATA[This paper presents an improved sliding mode control (SMC) strategy for robotic manipulators by introducing a novel exponential integral-based adaptive gain law, referred to as integral sliding mode control (ISMC). The proposed approach dynamically adjusts the switching gain KKK in real-time, based on the accumulated system error, thereby effectively reducing chattering while preserving system robustness. Unlike many existing methods, the ISMC strategy eliminates the need for state observers or complex estimation techniques, simplifying implementation. Theoretical analysis is provided using Lyapunov stability theory, ensuring global convergence. Simulation results on 2-DOF and 3-DOF robotic arms demonstrate superior tracking accuracy and smoother control signals compared to conventional SMC approaches. This work contributes a lightweight yet effective SMC enhancement with practical benefits for real-world robotic applications.]]>
<![CDATA[Edge-aware distilled segmentation with pseudo-label refinement for autonomous driving perception ]]>
<![CDATA[Indarto, Novelio Putra]]>;
<![CDATA[Natan, Oskar]]>;
<![CDATA[Dharmawan, Andi]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 14, No 3: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v14i3.pp376-386
<![CDATA[Achieving precise semantic segmentation is essential for enabling real-time perception in autonomous systems, yet leading approaches typically require substantial annotated data and powerful hardware, restricting their use on devices with limited resources. This work introduces an efficient segmentation framework that integrates pseudo-label refinement, knowledge distillation, and entropy-based confidence filtering to train compact student networks suitable for edge deployment. High-quality pseudo-labels are first produced by a robust teacher network, then further improved using a dense conditional random field to boost spatial consistency. An entropy-based selection mechanism removes unreliable predictions, ensuring that only the most trustworthy labels guide the student model's training. The use of knowledge distillation effectively transfers detailed semantic understanding from the teacher to the student, enhancing accuracy without added computational overhead. Experimental results with multiple EfficientNet backbones reveal that this pipeline improves segmentation accuracy and output clarity, while also supporting real-time or near real-time inference on CPUs with limited processing power. Extensive ablation and qualitative studies further confirm the method's robustness and flexibility for real-world edge applications.]]>
<![CDATA[Humanoid robot balance control system during backward walking using linear quadratic regulator ]]>
<![CDATA[Arsyi, Muhammad]]>;
<![CDATA[Dharmawan, Andi]]>;
<![CDATA[Sumbodo, Bakhtiar Alldino Ardi]]>;
<![CDATA[Auzan, Muhammad]]>;
<![CDATA[Istiyanto, Jazi Eko]]>;
<![CDATA[Natan, Oskar]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 14, No 3: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v14i3.pp320-330
<![CDATA[Humanoid robots are designed to replicate human activities, including tasks in hazardous environments. However, maintaining balance during backward walking remains a significant challenge due to center of mass (CoM) shifts beyond the support polygon and limited knee joint motion. This study proposes a control strategy that integrates a linear quadratic regulator (LQR) with optimized walking patterns to enhance dynamic stability. The approach combines LQR-based control with CoM trajectory planning to ensure safe and stable backward walking. The methodology includes inverse kinematics for generating walking patterns and the use of Inertial Measurement Unit (IMU) sensors to estimate the CoM trajectory. LQR parameters were tuned through simulation to improve responsiveness to disturbances. Evaluation metrics focused on CoM deviation, rise time, settling time, and overshoot. Experimental results demonstrate that the proposed LQR system effectively maintains the CoM within 5% of the support polygon boundary. The system achieved rise times under one second and settling times below two seconds, while minimizing pitch and roll overshoots. Compared to proportional control, the proposed method significantly improves stability and reduces the risk of falling. This research advances control strategies for humanoid robots, contributing to improved mobility and operational safety. Moreover, it supports Sustainable Development Goal (SDG) 9 by promoting innovation in intelligent robotic systems that can assist in complex or high-risk environments.]]>
<![CDATA[ADC-LIO: A direct LiDAR-inertial odometry method based on adaptive distortion covariance ]]>
<![CDATA[Yang, Lixiao]]>;
<![CDATA[Feng, Youbing]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 14, No 3: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v14i3.pp399-408
<![CDATA[Focusing on the localization challenges for robots in dynamic navigation environments, this study proposes a direct LiDAR-inertial odometry (LIO) system named ADC-LIO, which achieves robust pose estimation and accurate map reconstruction using adaptive distortion covariance. ADC-LIO is engineered to address uncertain motion patterns in autonomous mobile robots, effectively integrating LiDAR scan undistortion within the Kalman filtering update process by embedding an iterative smoothing process and a backpropagation strategy. The ADC-LIO architecture enhances point cloud accuracy, improving the system's overall performance and robustness. In addition, an adaptive covariance processing method is developed to resolve motion-induced sensing uncertainties, which calculates different covariances according to the error characteristics of the point cloud. This method enhances the constraints of high-quality point clouds, reduces the limitations on low-quality point clouds, and utilizes information more effectively. Experiments on the publicly available NTU-VIRAL dataset validate the effectiveness of ADC-LIO, which improves pose estimation accuracy and reduces absolute position errors compared to other state-of-the-art methods, including FAST-LIO, Faster-LIO, FR-LIO, and Point-LIO. The proposed ADC-LIO is an appealing odometry method that delivers accurate, real-time, and reliable tracking and map-building results, posing a practical solution for robotic applications in structured indoor and GPS-denied outdoor environments.]]>
<![CDATA[Optimal battery sizing using modified spider monkey optimization in grid connected microgrids ]]>
<![CDATA[Fatima, Meraj]]>;
<![CDATA[Subbamma, Manne Rama]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 14, No 3: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v14i3.pp356-365
<![CDATA[Microgrids (MGs) must have optimally sized storage and renewable energy sources to operate efficiently, economically, and reliably. MG may benefit from optimization techniques in their scheduling and sizing since they have a variety of energy sources with varying availability conditions and necessary costs. In this research, a novel modified spider monkey-based energy management system (MSM-EMS) has been proposed by increasing the photovoltaic (PV) or battery energy storage system (BESS) module capacity while minimizing grid connectivity dependency. The fundamental idea behind the proposed approach is greater dependability at the lowest feasible cost. By taking into account the BESS utilization factor and PV forced outage rates in a MG, the method becomes more realistic. Despite the absence of renewable energy sources and the grid, the proposed strategy provided critical loads according to schedule while maintaining reserve margins. Experimental findings demonstrate that the modified spider monkey optimization (MSMO)-based algorithm can determine the best BESS size and PV depending on cost. In comparison to particle swarm optimization (PSO) of $2756.1 and ABC of $2912.65, the ideal cost for EMS-MSMO is $2215.77 which is relatively low compared to the existing technique. As a result, the suggested MSMO algorithm and innovative energy management system has been optimized along with PV and battery dimensions.]]>
<![CDATA[Antecedents and consequences of memorable experience in the airline industry: service robots versus human staff ]]>
<![CDATA[Hwang, Jinsoo]]>;
<![CDATA[Choe, Ja Young (Jacey)]]>;
<![CDATA[Joo, Kyuhyeon]]>;
<![CDATA[Kim, Jinkyung Jenny]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 14, No 3: December 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v14i3.pp409-417
<![CDATA[The study aims to examine the type of service providers, such as service robots and human staff, as a potential moderator in the relationship between SERVQUAL and memorable experience in the airport industry. In order to verify 15 hypotheses, data were collected from 313 travelers who acquired information from service robots and 313 travelers who acquired information from human staff at the airport. The results of data analysis revealed that the five sub-dimensions of SERVQUAL, including tangibles, reliability, responsiveness, assurance, and empathy, enhance memorable experience. In addition, a memorable experience has a positive effect on customer satisfaction, which subsequently influences attitude and intention to use. In addition, the type of service providers moderated the links between i) responsiveness and memorable experience and ii) empathy and memorable experience.]]>
