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.
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<![CDATA[Combining optimization and dynamic movement primitives for planning energy optimal forestry crane motions ]]>
<![CDATA[La Hera, Pedro]]>;
<![CDATA[Morales, Daniel Ortíz]]>;
<![CDATA[Mendoza-Trejo, Omar]]>
<![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.pp180-193
<![CDATA[Forestry cranes are an important tool for safe and efficient timber harvesting with forestry machines. However, their complex manual control often led to inefficiencies and excessive energy usage, due to the many joysticks and buttons that must be used in a precise sequence to perform efficient movements. To address this, the industry is increasingly turning to partial automation, making manual control more intuitive for the operator and, consequently, achieving improvements in energy efficiency. This article introduces a novel approach to energy-optimal motion planning that can be used along with a feedback control system to automate crane motions, taking over portions of the operator’s work. Our method combines dynamic movement primitives (DMPs) and an energy-optimization algorithm. DMPs is a machine learning technique for motion planning based on human demonstrations, while the optimization algorithm exploits the crane’s redundancy to find energy-optimal trajectories. Simulation results show that DMPs can replicate human-like controlled motions with a 25% reduction in energy consumption. However, our energy optimization algorithm shows improvements of over 40%, providing substantial energy savings and a promising pathway towards environmentally friendly partially automated machines.]]>
<![CDATA[Robot navigation on inclined terrain using social force model ]]>
<![CDATA[Daffa, Muhammad Fariz]]>;
<![CDATA[Dewantara, Bima Sena Bayu]]>;
<![CDATA[Setiawardhana, Setiawardhana]]>
<![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.pp131-139
<![CDATA[This research introduces an innovative approach to address the limitations of the commonly used social force model-based robot navigation method on flat terrain when applied to sloped terrain. The incline of the terrain becomes a crucial factor in calculating the robot’s steering output when navigating from the initial position to the target position while avoiding obstacles. Therefore, we propose a social forced model-based robot navigation system that can adapt to inclined terrain using inertial measurement unit sensor assistance. The system can detect the surface incline in real time and dynamically adjust friction and gravitational forces, ensuring the robot’s speed and heading direction are maintained. Simulation results conducted using CoppeliaSim show a significant improvement in speed adjustment efficiency. With this new navigation system, the robot can reach its destination in 59.935089 seconds, compared to the conventional social forced model which takes 63.506442 seconds, the robot is also able to reduce slip to reduce wasted movement. This method shows the potential of implementing a faster and more efficient navigation system in the context of inclined terrain.]]>
<![CDATA[Development of Arduino-based high heat detector temperature control prototype for household appliances ]]>
<![CDATA[Casinillo, Rhoda Mae L.]]>;
<![CDATA[So, Allecia Leona A.]]>;
<![CDATA[Mandaya, Maezel V.]]>;
<![CDATA[Dabalos, Sonny Adrian J.]]>;
<![CDATA[Enriquez, Mark Ceasar S.]]>;
<![CDATA[Cane, Jas Felicisimo]]>
<![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.pp140-159
<![CDATA[In the Philippines, fires are a widespread concern, with plenty of incidents attributed to electrical appliances. These incidents are a leading cause of non-open flame fires in the country, highlighting the urgent need for preventative measures. Existing devices could only trigger an alarm at 100 °C without shutting off the appliance automatically. To address these limitations, the researchers aimed to develop a high heat detector with 95% detection accuracy and less than 5% error in detecting high heat. This device used an Arduino Uno Board and relay to trigger an automated power-off mechanism in appliances experiencing high heat. Temperature changes were detected, and alarms were activated using an LM35 temperature sensor and buzzer. The accuracy of the LM35 sensor was assessed through hot bath tests, which included 12 trials at each temperature level between 80 °C and 150 °C with 10 °C intervals. The prototype’s performance revealed an average error rate of 1.13% and an average standard deviation of 0.9403. The computed F1 Score of 98% indicated that the prototype fulfilled the objectives. Functionality tests confirmed that the prototype successfully achieved its intended goal by shutting off the appliance when the threshold temperature was reached and enabling its operation otherwise.]]>
<![CDATA[Kinematic modelling of three link robot manipulator and joint torque optimization using genetic algorithm in MATLAB ]]>
<![CDATA[Sahay, Neeta]]>;
<![CDATA[Chattopadhyay, Subrata]]>
<![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.pp160-167
<![CDATA[This research article presents the non-linear dynamic of a three-link robotic manipulator formulated by the Newton-Euler method. The planar manipulator is composed of three links and three revolute joints rotating about the z-axis. The three nonlinear non-homogeneous dynamic equations have been solved graphically with the help of MATLAB by phase variable method. The work represents the graphical solution of the transient response of angular position, and angular velocity of each link member for a predetermined interval of time. With the help of simulated value from MATLAB, torque characteristics have been determined for different torque ratios and optimum torque has been derived using a genetic algorithm to move the manipulator in a proper direction.]]>
<![CDATA[Development of robot motion direction based on microcontroller with compass sensor ]]>
<![CDATA[Seke, Fransiskus Royke]]>;
<![CDATA[Tamba, Ibadja Parsaoran]]>
<![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.pp122-130
<![CDATA[This research brings innovation to the motion and navigation system of the ‘DK-ONE’ robot. In the 2021 Indonesian ‘Search and Rescue’ robot contest, the ‘DK-ONE’ robot faced difficulties moving towards the target room. The issue was attributed to an unbalanced frame construction and friction between the robot’s legs and the arena floor, leading to leg slippage. This resulted in a mismatch between the programmed number of steps for the robot and the desired path to the target space, causing errors in the robot’s system. To address these problems, researchers conducted a study aimed at enabling the ‘DK-ONE’ robot to accurately determine its direction of motion. This research followed the waterfall method, involving stages such as system analysis, design, coding, testing, and supporting phases. The study was carried out in the integrated laboratory of the Department of Electrical Engineering Education. The development of the robot’s motion direction using a compass sensor significantly improved stability while walking on straight, flat, and uneven paths. The robot no longer experienced errors in its motion direction and remained on the intended path. As a result, the increased efficiency in robot motion also positively impacted the structural efficiency and energy consumption of the robot.]]>
<![CDATA[Distributed and autonomous multi-robot for task allocation and collaboration using a greedy algorithm and robot operating system platform ]]>
<![CDATA[Tamali, Abderrahmane]]>;
<![CDATA[Amardjia, Nourredine]]>;
<![CDATA[Tamali, Mohammed]]>
<![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.pp205-219
<![CDATA[Research investigations in the realm of micro-robotics often center around strategies addressing the multi-robot task allocation (MRTA) problem. Our contribution delves into the collaborative dynamics of micro-robots deployed in targeted hostile environments. Employing advanced algorithms, these robots play a crucial role in enhancing and streamlining operations within sensitive areas. We adopt a tailored GREEDY approach, strategically adjusting weight parameters in a multi-objective function that serves as a cost metric. The objective function, designed for optimization purposes, aggregates the cost functions of all agents involved. Our evaluation meticulously examines the MRTA efficiency for each micro-robot, considering dependencies on factors such as radio connectivity, available energy, and the absolute and relative availability of agents. The central focus is on validating the positive trend associated with an increasing number of agents constituting the cluster. Our methodology introduces a trio of micro-robots, unveiling a flexible strategy aimed at detecting individuals at risk in demanding environments. Each micro-robot within the cluster is equipped with logic that ensures compatibility and cooperation, enabling them to effectively execute assigned missions. The implementation of MRTA-based collaboration algorithms serves as an adaptive strategy, optimizing agents' mobility based on specific criteria related to the characteristics of the target site. ]]>
<![CDATA[Development of an unmanned ground vehicle for seed planting ]]>
<![CDATA[Owoeye, Samuel Oluyemi]]>;
<![CDATA[Durodola, Folasade]]>;
<![CDATA[Bode-Okunade, Abdulsalam Babajide]]>;
<![CDATA[Alkali, Ahmed Baba]]>;
<![CDATA[Okonkwo, Chibuike Timothy]]>
<![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.pp168-179
<![CDATA[As global population growth intensifies the demand for sustainable food production, the application of robotics to agriculture emerges as a promising solution. This research focuses on the design, development, and deployment of an unmanned ground vehicle for seed planting, also known as a robotic seed planter. The robotic seed planter automates seed planting processes, offering advantages such as increased accuracy, reduced labour requirements, and optimal resource usage. Parametric Technology Corporation (PTC) Creo was used for the structural design, Proteus 8.14 for the circuitry design, and Arduino IDE 2.0 with Visual Studio Code for the programming. The design incorporates seed metering and drilling mechanisms guided by intelligent systems. Results show exceptional accuracy in seed placement (94%), operational efficiency, and adaptability to diverse conditions, with energy consumption relatively low. The planter is equipped with a web application for remote monitoring and control. The application is hosted on one of the microcontrollers and WebSockets protocol is utilized for inter-microcontroller communication. It offers an auto mode for automated planting and Manual mode for easier manoeuvrability. The findings of this study demonstrate the robotic seed planter’s transformative impact on precision agriculture, providing a glimpse into the future of efficient and sustainable farming operations.]]>
<![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[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[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.]]>
