1,721,306 research outputs found
Unlocking robotic perception: comparison of deep learning methods for simultaneous localization and mapping and visual simultaneous localization and mapping in robot
No full textSimultaneous Localization and Mapping (SLAM) and Visual SLAM are crucial technologies in robotics, allowing autonomous systems to navigate and comprehend their environment. Deep learning (DL) has become a powerful tool in driving progress in these areas, providing solutions that improve accuracy, efficiency, and resilience. This article thoroughly analyzes different deep learning techniques designed explicitly for SLAM and Visual SLAM applications in robotic systems. This work provides a detailed overview of DL roles in SLAM and VSLAM and emphasizes the differences between these two fields. Five powerful DL methods are investigated: Convolutional Neural Networks in extracting features and understanding meaning, Recurrent Neural Network in modeling temporal relationships, Deep Reinforcement Learning in developing exploration strategies, Graph Neural Network in modeling spatial relationships, and Attention Mechanisms in selectively processing information. In this research, we will examine the advantages and disadvantages of each approach in relation to robotic applications, taking into account issues such as real-time performance, resource restrictions, and adaptability to various situations. This article seeks to guide researchers and practitioners in selecting suitable deep learning algorithms to improve the capabilities of SLAM and Visual SLAM in robotic systems by combining ideas from recent research and actual implementations. The popular types of each concerned DL will be synthesized with the discussion of pros and cons
Yaw/Heading optimization by Machine learning model based on MEMS magnetometer under harsh conditions
No full textThe paper's main goal is to accomplish a high accuracy of yaw/heading by Machine Learning approach when the motion range of vehicle/device calibration is limited. The nonlinear Random Forest (RF) Regression with proper training has a high potential to deal with the magnetometer uncertainty before calibration and during iron distortion cases. The proposed solution solely requires the magnetometer without other sensor's support. A Pan Tilt Unit-C46 (PTU-C46) with high precise positioning was used as a reference heading value to label the corresponding magnetic features in the learning model. The proposed approach helps yaw estimation to be carried out under harsh conditions, which resolve many difficulties in orientation tracking since the magnetometer is susceptible to hard iron and soft iron in the environment. In addition, many mechanical devices work only within the specific range and waste their dynamic motion around two axes or more just for calibration. Thus, the research focuses on the level rotation calibration around Z-axis within the restricted range of motion for practical application. The experiment was carried out using a low-cost platform equipped with Micro-Electro-Mechanical System (MEMS) sensors as gyroscope, accelerometer, and magnetometer. The 9 Degree of Freedom (DoF) Madgwick was implemented into the Microcontroller to compare with the proposed model. The sensor fusion can track the yaw value after the level calibration despite various error conduction. The RF model accomplishes a superior result with more stability and more minor error. Under iron disturbance or calibration absence, the ML model still maintains the good tracking command with maximum Mean Square Error of about 0.3°, while the Madgwick is unsuccessful in heading measurement due to huge error in these circumstances
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Digital Twin-Based Real-Time Monitoring System for Safety of Multiple Laptops in Working Environment
No full textOverheating is a significant issue for laptops, especially in working environments where multiple laptops are utilized to launch heavy programs without the user's presence frequently. The proposed monitoring method is based on a digital twin (DT) system in a workstation that monitors the heat power loss of the battery, relying on the measurements of the battery current, the central processing units (CPUs) temperatures, and graphics processing units (GPUs) temperatures. Other personal computer (PC) laptops deliver their data via transmission control protocol (TCP)/Internet protocol (IP). The workstation sends a query message, allowing each PC to transfer the necessary information. The virtual system handles the received data to proceed with the alert system for warning if these parameters overcome the concerned threshold. The DT system is implemented into a Dell workstation based on MATLAB-Simulink to manage the data from ten other PCs in the experiment. Power loss is calculated in the DT Simulink system based on the electrical circuit of the PC in plugged-in mode and discharge mode. Together with other factors, the system successfully monitors and detects the current situation with a specific alert function. The monitored parameters can be observed for each setting-up period, which allows the manager to comprehend the condition state during a specific time
New Artificial Intelligence Approach to Inclination Measurement Based on MEMS Accelerometer
No full textThe article presents a research of angular orientation based on a microelectromechanical system (MEMS) accelerometer by using machine learning (ML) and deep learning (DL) model with architectures of deep neural networks (DNNs). In the industrial environment, artificial intelligence (AI) plays a crucial role in automation which is a potential solution for better performance of inclinometer. This article was carried out to apply this intelligent model on the inertial measurement unit to accomplish the angular position. The experiment shows that the ML model correctly learns the relationship between acceleration and tracking angles via polynomial regression with an R-square of 0.98. The employed DL model with four hidden layers of ten neurons achieves an accuracy of 99.99 % and almost a nonerror performance. The acceleration acquisitions were obtained from MEMS accelerometer LSM9DS1 at a frequency of 50 Hz via microcontroller STM32F401RE. The ML and DNN models were designed based on the platform Tensorflow with high processing accuracy. The Pan-Tilt Unit was used as the angle reference for static and dynamic tests. The traditional technique is used for comparison as well as verification of the proposed models. The DL model has better precision over the ML model due to its high structure level with updating weight and error optimization from the neural network structure. Meanwhile, ML shows more stable results in dynamic circumstances
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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