IAES International Journal of Robotics and Automation (IJRA)
Not a member yet
460 research outputs found
Sort by
Transport platform stabilization mechanism using controlled suspension
Get PDFIn this paper the authors present the development of a novel transport mechanism designed to perform gravity survey work on difficult terrain. Thus, in the first part of the paper the authors present review and analysis of existing patents and commercial developments of transport platforms capable of stabilizing loads while travelling in urban environments with potholes and steps. In the second part we present technical solution of a steerable suspension with a torsion bar as an elastic element based on the elimination of the drawbacks of the existing developments. The core feature of this development is the potential ability to adapt the suspension to different types of surfaces by changing the elastic characteristics of the torsion bar. We also propose an alternative to the generally accepted kinematic scheme by using a conical gearbox, which allows to achieve a tight arrangement of suspension mechanisms within the dimensions of the transport platform. In addition, authors propose the stabilization mechanism, that allows to change the clearance of the transport platform and provides stabilization of the gravity exploration research equipment, characterized by sensitivity to deviations from the vertical
An approach for modern gardening through monitoring and maintenance of plant health
Get PDFThe study explores the use of internet of things (IoT) devices in agriculture to improve sustainable practices and environmental concerns. It uses the ESP8266 microcontroller and the Blynk platform to create a revolutionary plant health monitoring and automated care system. The system is designed to handle continuous monitoring and plant maintenance in various environmental conditions. Sensors measuring light, temperature, humidity, and soil moisture are strategically placed to receive real-time data. The ESP8266 microcontroller analyzes this information and links it to the Blynk cloud for accessibility via mobile or web applications. The system is effective in monitoring ideal growing conditions, such as soil moisture and weather conditions. Automated care elements like irrigation and supplemental lighting have been shown to improve plant growth and health. The study contributes to smart farming by offering an affordable and easy way to automate and monitor plant health, demonstrating how IoT technologies can enhance agricultural practices, conserve resources, and enable remote management of plant ecosystems
Robot indoor navigation: comparative analysis of LiDAR 2D and visual SLAM
Get PDFRobot indoor navigation has become a significant area of research and development for applications such as autonomous robots, smart homes, and industrial automation. This article presents an in-depth comparative analysis of LiDAR 2D and visual sensor simultaneous localization and mapping (SLAM) approaches for robot indoor navigation. The increasing demand for autonomous robots in indoor environments has led to the development of various SLAM techniques for mapping and localization. LiDAR 2D and visual sensor-based SLAM methods are widely used due to their low cost and ease of implementation. The article provides an overview of LiDAR 2D and visual sensor-based SLAM techniques, including their working principles, advantages, and limitations. A comprehensive comparative analysis is conducted, assessing their capabilities in terms of robustness, accuracy, and computational requirements. The article also discusses the impact of environmental factors, such as lighting conditions and obstacles, on the performance of both approaches. The analysis’s findings highlight each approach’s strengths and weaknesses, providing valuable insights for researchers and practitioners in selecting the appropriate SLAM method for robot indoor navigation based on specific requirements and constraints
Use of artificial intelligence in banknote reconstruction
Get PDFBanknotes may be damaged during various events, such as floods, fires, insect infestations, and mechanical or manual shredding. Disaster victims might need to perform banknote reconstruction when applying for currency exchange, or investigative agencies might need to conduct such reconstruction during evidence collection. When the number of banknote fragments is small, they can be manually assembled; however, when this number is large, manual assembly becomes increasingly difficult and time-consuming. Therefore, an automated and effective method is required for banknote reconstruction. The process of banknote reconstruction can be considered similar to solving a large-scale jigsaw puzzle. This study employed an artificial intelligence (AI) system to reconstruct damaged banknotes. A robotic arm was used to replace manual separation and automated digital image processing techniques, and AI image registration technology, deep learning, and logical operations were utilized. A deep convolutional neural network was used to estimate the relative homography between images, and fragmented banknotes were mapped to a reference banknote for image transformation, thereby reconstructing the damaged banknotes. Additionally, a repetitive matching method was established to optimize the matching results to achieve the best possible mapping and enhance validation efficiency
Vision-based approach for human motion detection and smart appliance control
Get PDFThis 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
The use of artificial intelligence in interrogations: voluntary confession
Get PDFInterrogation 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
Bipedal robot center of pressure feedback simulation for center of mass learning
Get PDFThis 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
A hybrid gradient climbing algorithm for a swarm robot-based gas leak detector
Get PDFMethane emissions from leak sources can have a negative climate impact, in addition to contributing to the risk of explosions in urban environments. These risks can be minimized by developing systems that provide for an accurate and timely detection and localization of a gas leakage point. This research used a swarm of robots to detect and locate a leakage point. The localization algorithm derives from further optimization of the gradient climbing algorithm using fireflies acting as opportunistic agents. Firefly agents are characterized by their bioluminescent communication which guides them to dynamically adjust their positions and intensities based on the quality of the gradient information available to them. The proposed research focuses on enhancing gas leak detection through the development of a hybrid gradient climbing algorithm. This algorithm integrates gradient climbing techniques with swarm intelligence, utilizing the strengths of both approaches. This simulation resulted in the hybrid algorithm leading to a reduced convergence time and path lengths when compared to the swarm without opportunistic agents. The suggested approach can be important especially in gas distribution systems or in areas where human intervention is considered to be unsafe
A 2D path-planning performance comparison of RRT and RRT* for unmanned ground vehicle
Get PDFIn recent years, path-planning has gained significant attention as mobile robots are used in various applications. Several factors determine the optimal path for a mobile robot, including accuracy, length of path, execution time, and turns. Among all planners, sampling-based planners such as rapidly exploring random trees (RRT) and rapidly exploring random trees-star (RRT*) are extensively used for mobile robots. The aim of this paper is the review and performance of these planners in terms of step size, execution time, and path length. All planners are implemented on the Jackal robot in a static environment cluttered with obstacles. Performance comparisons have shown that the reduction of step size results in exploring a greater number of nodes in both algorithms, increasing the probability of each extension succeeding. However, this causes the tree to become denser in both algorithms due to the more explored nodes. The RRT planner requires less execution time when the step size and iteration count are equal to RRT* planners. Moreover, performance plots of both algorithms show that RRT* provides an optimal and smooth path than RRT
A novel structure of magnetic geared generator in dual-rotor wind turbine
Get PDFVariable-speed constant-frequency generating systems are commonly employed in wind turbines to enhance efficiency and minimize losses. Additionally, the utilization of dual-rotor wind turbines enables the capture of a greater amount of wind energy, leading to a significant increase in efficiency. Traditionally, dual-rotor wind turbines are managed by a full-scale power converter, and the rotor current is transmitted through brushes, which substantially raises the system's cost. To address these challenges, this study introduces a novel configuration that enables power control with a smaller power converter. In contrast to conventional dual-rotor wind turbines that generate power using both rotors, the proposed structure designates one rotor as a system controller. Apart from these benefits, the proposed structure greatly enhances conversion performance by notably improving the power factor. A comparison with existing configurations described in literature is conducted to demonstrate the superiority of the proposed structure