IAES International Journal of Robotics and Automation (IJRA)
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Robot Gaussian-historical relocalization: inertial measurement unit-LiDAR likelihood field matching
Get PDFRobot localization is a foundational technology for autonomous navigation, enabling task execution and adaptation to dynamic environments. However, failure to return to the correct pose after power loss or sudden displacement (the “kidnapping” problem) can lead to critical system failures. Existing methods often suffer from slow relocalization, high computational cost, and poor robustness to dynamic obstacles. We propose a novel inertial measurement unit (IMU)-LiDAR fusion relocalization framework based on Gaussian historical constraints and adaptive likelihood field matching. By incorporating IMU-derived yaw constraints and modeling historical poses within a 3σ Gaussian region, our method effectively narrows the LiDAR search space. Curvature and normal vector-based feature extraction reduces point cloud volume by 50–70%, while dynamic obstacle filtering via multi-frame differencing and neighborhood validation enhances robustness. An adaptive spiral search strategy further refines pose estimation. Compared to ORB-SLAM3 and adaptive Monte Carlo localization (AMCL), our method maintains comparable accuracy while significantly reducing relocalization time and CPU usage. Experimental results show a relocalization success rate of 84%, average time of 1.68 seconds, and CPU usage of 38.4%, demonstrating high efficiency and robustness in dynamic environments
Design of low-power, high-speed approximate 4:2 compressors for efficient partial product reduction in multipliers
Get PDFPartial product reduction becomes the main task in the multiplication process. Therefore, the partial product stages of multipliers are reduced with the usage of compressors, by using compressors in the multiplier. Using compressors in the multiplier circuit significantly impacts multiplier performance. Approximate compressors are crucial for achieving better design metrics in parallel multipliers. This paper proposes to create various new approximate 4:2 compressor circuits. A trade-off is made between the performance and accuracy of this approximate circuit design approach. The proposed designs have been implemented using XOR-XNOR gates with a 2-to-1 multiplexer, and also XOR-XNOR gates with transmission gates. All these circuits have been simulated using Cadence in different technological nodes. Compared with the existing technique, the proposed 4:2 approximation compressor provides 51.4% power reduction and 26.45% delay reduction for 45 nm equipment
Fuzzy logic assessment of X-ray tube risks in robotic C-arm angiography: a failure mode and effect analysis study
Get PDFThis 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 development of knee rehabilitation robot
Get PDFThis 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
Combining optimization and dynamic movement primitives for planning energy optimal forestry crane motions
Get PDFForestry 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
Development of Arduino-based high heat detector temperature control prototype for household appliances
Get PDFIn 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
An introduction to using QR codes in web portals for synchronizing calendar events over phones
Get PDFAn 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%
The future of artificial intelligence-driven robotics: applications and implications
Get PDFArtificial 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
Adjusted linear quadratic regulator-proportional-derivative control of Quanser’s three degrees of freedom helicopter based on flower pollination algorithm under external disturbances
Get PDFExternal 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
Development of robot motion direction based on microcontroller with compass sensor
Get PDFThis 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