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[The use of artificial intelligence in interrogations: voluntary confession ]]>
<![CDATA[Wu, Yi-Chang]]>;
<![CDATA[Liu, Yao-Cheng]]>;
<![CDATA[Huang, Ru-Yi]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 2: June 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v13i2.pp113-121
<![CDATA[Interrogation is a crucial step in the investigation of criminal acts. Artificial intelligence has been used to increase the efficiency of interrogation. In this study, we developed a confession probability identification system to help investigators analyze the emotions of their interrogees while they are answering questions and determine the probability of them confessing. Based on these analysis results along with their own experience, investigators may adjust the content and direction of their interrogations to penetrate the interrogees’ defenses. The proposed system uses OpenFace and FaceReader to capture data and incorporates the multi-grained cascade forest (gcForest) and long short-term memory (LSTM) algorithms for deep learning. Our results indicated that the recognition accuracy of the gcForest algorithm exceeded that of the LSTM algorithm, which is consistent with the fact that the gcForest algorithm is more suitable for smaller sample sizes. In addition, heart-rate-based assessment may lead to erroneous determination of whether an interrogatee is telling the truth or lies because their heart rate may increase as a result of emotional responses.]]>
<![CDATA[Experimental results on position and path control of an automated guided vehicle using fixed camera at ceiling and color markers ]]>
<![CDATA[Pungle, Ramesh]]>;
<![CDATA[Andhare, Atul]]>;
<![CDATA[Pungle, Durva]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v13i4.pp391-400
<![CDATA[This article presents the results of experiments on path planning and control of automated guided vehicles (AGV) using single, fixed ceiling mounted, monocular cameras and colored markers. The camera employed in the system serves as both a sensor and controller. Initially, the working environment is structured using colored markers for given applications. For every new setup, structuring the environment is essential. The image processing algorithm identifies the colored markers and their positions, which are then utilized for path planning and segmentation. The actuation time required to transverse each segment is calculated and then AGV is actuated accordingly. A transformation or inverse mapping matrix (M), predetermined, is employed for calculating world coordinates from given image coordinates. Path planning and AGV control are across various paths, both with and without static obstacles, in real-time applications. The colored marker detection and recognition accuracy for the given setup have been found cent percentage while the AGV reaches the goal point with an error margin of around 3.9% on straight paths, both with and without obstacles.]]>
<![CDATA[The color features and k-nearest neighbor algorithm for classifying betel leaf image ]]>
<![CDATA[Hamdani, Hamdani]]>;
<![CDATA[Septiarini, Anindita]]>;
<![CDATA[Puspitasari, Novianti]]>;
<![CDATA[Tejawati, Andi]]>;
<![CDATA[Alameka, Faza]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 3: September 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v13i3.pp330-337
<![CDATA[Piper betle L. (betel) is a species that belongs to the genus Piper and is a type of medicinal plant that is quite well known to the general population. The varieties of the leaf color may distinguish are red, green, and black betel. However, consumers still need assistance determining the differences between the many types of betel leaf. Therefore, using image processing techniques, this research contributes to building a classification method for distinguishing betel leaves based on color attributes. This approach anoints for the region of interest detection, feature extraction, and classification. In addition, three different classifiers, naïve Bayes, support vector machine, and k-nearest neighbors (k-NN), were used during the classification process. The evaluation for this study used a percentage split to divide a total of 180 images between the training and testing phases. The method’s performance provided the highest accuracy value possible, 100%, by utilizing the color characteristics with the k-NN classifier.]]>
<![CDATA[Nonlinear Kalman filter for gyroscopic and accelerometer noise rejection of an unmanned aerial vehicle control strategy ]]>
<![CDATA[Arfa, Wassim]]>;
<![CDATA[Ben Jabeur, Chiraz]]>;
<![CDATA[Fathallah, Mourad]]>;
<![CDATA[Seddik, Hassene]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 2: June 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v13i2.pp194-204
<![CDATA[This study addresses timing issues inherent in traditional proportional-integral-derivative (PID) controllers for drone angle control and introduces an innovative solution, the adaptive PID flight controller, aimed at optimizing PID gains for improved performance in terms of speed, accuracy, and stability. To enhance the controller's robustness against noise and accurately estimate the system's state, a Kalman filter is incorporated. This filtering mechanism is designed to reject noise and provide precise state estimation, thereby contributing to the overall effectiveness of the adaptive PID flight controller in managing altitude dynamics for unmanned aerial vehicles (UAVs). The comparative methodology evaluates three configurations: a single PID controller for all three angles, two PID controllers dedicated to pitch/roll and yaw angles separately, and three PID sub-controllers for each angle (pitch, roll, and yaw). The study seeks to identify the most effective PID configuration in terms of stability, responsiveness, and accuracy while highlighting the added benefits of noise rejection and state estimation through the Kalman filter. This integrated approach showcases innovation and effectiveness, introducing a comprehensive solution not explored in previous research.]]>
<![CDATA[An overview of emerging trends in robotics and automation ]]>
<![CDATA[Sutikno, Tole]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 4: December 2023 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v12i4.pp405-411
<![CDATA[Robotics has experienced significant growth and development over the past few decades, with the first industrial robots introduced in the 1950s. As technology advances, robotics has become more intelligent, smart, and flexible, with the introduction of artificial intelligence (AI) and machine learning (ML). Robots are now being integrated into various fields, including healthcare, agriculture, transportation, and space exploration. Robots are set to revolutionize our daily lives, transforming interactions and work processes as technology advances. Emerging trends in robotics, such as AI and ML, soft robotics, and swarm robotics, can transform industries and improve efficiency. The future of robotics and automation promises safer workplaces, improved healthcare, and enhanced environmental sustainability. Society must adapt to this changing landscape, requiring continuous learning and upskilling to remain relevant in the workforce.]]>
<![CDATA[Faults-as-address simulation ]]>
<![CDATA[Hahanov, Vladimir]]>;
<![CDATA[Chumachenko, Svetlana]]>;
<![CDATA[Litvinova, Eugenia]]>;
<![CDATA[Hahanov, Ivan]]>;
<![CDATA[Ponomarova, Veronika]]>;
<![CDATA[Khakhanova, Hanna]]>;
<![CDATA[Kulak, Georgiy]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v13i4.pp452-468
<![CDATA[Fault-as-address-simulation (FAAS) is a simulation mechanism for testing combinations of circuit line faults, represented by the bit addresses of element logical vectors. The XOR relationship between the test set T and the truth table L of the element forms a deductive vector for fault simulation, using truth table addresses or the logic vector bits. Addresses are used in the simulation matrix to mark those n-combinations of input faults detected at the element's output. The columns of the simulation matrix are treated as n-row addresses to generate an element output row via a deductive vector. There is no transport of input faults to the element output, Only the 1-signals written in the non-input row coordinates of the circuit simulation matrix. The simulation matrix is initially filled with 1-signals along the main diagonal. The line faults detected on the test set of circuits are determined by the inverse of lines good values, which have 1-values in the matrix row corresponding to the output circuit element. The deductive vector is obtained by the XOR-relations between the test set and logical vector in three table operations. The advantage of the proposed FAAS mechanism is the predictable complexity of the algorithm and memory consumption for storing data structures when simulating a test set.]]>
<![CDATA[Bipedal robot center of pressure feedback simulation for center of mass learning ]]>
<![CDATA[Mayub, Afrizal]]>;
<![CDATA[Fahmizal, Fahmizal]]>;
<![CDATA[Lazfihma, Lazfihma]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 2: June 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v13i2.pp220-232
<![CDATA[This research aims to create a walking bipedal robot with center of pressure feedback simulation for the center of mass learning, describe its feasibility for learning, describe students' motivation to learn, and describe students' science literacy after using it. The research method used ADDIE (analysis, design, development, implementation, and evaluation). The research data was obtained using a motivation scale questionnaire, science literacy scale, and feasibility scale. The research sample was 48 people; after the research obtained, the simulation of bipedal robot pressure center feedback for center of mass learning can be implemented with the principle of the robot's center of mass detected on the sole of the robot's foot equipped with a force sensitive resistor (FSR) sensor, the position of the center of mass is visible on the monitor screen as a center of mass learning, so that it can motivate students to learn and improve students' science literacy. This can be seen from the feasibility scale score, motivation scale, and science literacy scale of 4.133, 4.072, and 4.067 (scale 1 to 5), respectively, in the "good" category.]]>
<![CDATA[Inverse kinematics of six degrees of freedom robot manipulator based on improved dung beetle optimizer algorithm ]]>
<![CDATA[Haohao, Ma]]>;
<![CDATA[As’arry, Azizan]]>;
<![CDATA[Haoyang, Zhang]]>;
<![CDATA[Ismail, Mohd Idris Shah]]>;
<![CDATA[Rashidi Ramli, Hafiz]]>;
<![CDATA[Zuhri, Mohd Yusoff Moh]]>;
<![CDATA[Delgoshaei, Aidin]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 3: September 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v13i3.pp272-282
<![CDATA[Inverse kinematics is a basic problem in robotics, which aims to solve the robot’s joint angles according to the end effector’s position and orientation. This paper proposed an improved spiral search multi-strategy dung beetle optimizer (DBO) algorithm for solving the inverse kinematics problem. The improved DBO algorithm considers not only the error between the target value and the current value but also the previous position of the robot to ensure minimum displacement during the movement. To solve the end position error and orientation error of the robot end effector more accurately, the quaternion is introduced as a penalty factor in the optimization objective function, which is of great significance for reducing the orientation error. Through the improved DBO algorithm, the position error is still accurate, and the orientation error is reduced from 9.5901 to 1.8718. Experimental results show that the proposed algorithm outperforms other swarm-intelligent algorithms in terms of accuracy and convergence speed. Overall, the proposed spiral search multi-strategy DBO algorithm provides an effective and efficient solution to the inverse kinematics problem in robotics.]]>
<![CDATA[Switching regulator based on an adaptive DC-DC buck converter for a lithium-ion battery charging interface ]]>
<![CDATA[Rahali, Ahmed]]>;
<![CDATA[El Khadiri, Karim]]>;
<![CDATA[Qjidaa, Hassan]]>;
<![CDATA[Tahiri, Ahmed]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 3: September 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v13i3.pp351-360
<![CDATA[A switching regulator based on an adaptive DC-DC buck converter for a Li-ion battery charging interface is introduced in this paper with the aim of improving the efficiency of charging the Li-ion battery during the whole charging process. By using the battery voltage as feedback, an adaptive reference is generated. This reference is employed by the converter, which is in continuous conduction mode (CCM), to produce a wide adaptive output voltage that closely tracks the battery voltage, intended to serve as the power source for the multimode charging interface. The converter was implemented in a 180 nm complementary metal oxide semiconductor (CMOS) process and simulated using the Cadence Virtuoso tool. With an input voltage of 5 V and a switching frequency selected at 500 kHz, the simulation results show that the converter produces different charging currents for each battery charging mode, and an adaptive output voltage ranging from 2.8 V to 4.38 V, with the current ripple of 38 mA in CC mode and voltage ripple factor less than 1% in constant voltage (CV) mode. The average converter efficiency is 83.5%.]]>
<![CDATA[Design and development of knee rehabilitation robot ]]>
<![CDATA[Sharma, Devashish]]>;
<![CDATA[Shaik, Sahil Ahamed]]>;
<![CDATA[Rajagopal, Saran]]>;
<![CDATA[Mohan, Manju]]>;
<![CDATA[Ramanathan, Kuppan Chetty]]>;
<![CDATA[Lingampally, Pavan Kalyan]]>
<![CDATA[ IAES International Journal of Robotics and Automation (IJRA) Vol 13, No 4: December 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijra.v13i4.pp423-431
<![CDATA[This research presents a comprehensive design and analysis of a knee rehabilitation platform aimed at aiding individuals with knee dysfunction. Dysfunction in the knee joint can lead to an imbalance in gait and posture during activities of daily living (ADLs) such as standing, walking, and running. This study focuses on developing a 2-degree-of-freedom (2-DoF) knee rehabilitation device capable of mimicking linear and angular movements. A slider mechanism-based knee rehabilitation device is developed and simulated alongside various other mechanisms. The proposed mechanism achieves 32.5° of flexion for a linear movement of 0.45 m within 6 seconds, outperforming other mechanisms. To validate simulation results, a 3D-printed model is fabricated, and experimental studies are conducted under no-load conditions, showing close alignment with simulation outcomes with a deviation of ±5%. The device’s key features include portability, compliance, compactness, and enhanced stiffness. Future research will involve conducting pilot studies to further evaluate the practical efficacy and potential enhancements of the proposed knee rehabilitation platform.]]>
