rss_2.0Journal of Automation, Mobile Robotics and Intelligent Systems FeedSciendo RSS Feed for Journal of Automation, Mobile Robotics and Intelligent Systems of Automation, Mobile Robotics and Intelligent Systems Feed Research of Motion of Lightweight Wheeled Mobile Robot on Various Types of Soft Ground – A Case Study<abstract> <title style='display:none'>Abstract</title> <p>A problem of influence of three types of soft ground on longitudinal motion of a lightweight four-wheeled mobile robot is considered. Kinematic structure, main design features of the robot and its dynamics model are described. A numerical model was elaborated to simulate the dynamics of the robot’s multi-body system and the wheel-ground interaction, taking into account the soil deformation and stresses occurring on the circumference of the wheel in the area of contact with the deformable ground. Numerical analysis involving four velocities of robot motion and three cases of soil (dry sand, sandy loam, clayey soil) is performed. Within simulation research, the motion parameters of the robot, ground reaction forces and moments of force, driving torques, wheel sinkage and slip parameters of wheels were calculated. Aggregated research results as well as detailed results of selected simulations are shown and discussed. As a result of the research, it was noticed that wheel slip ratios, wheels’ sinkage and wheel driving torques increase with desired velocity of motion. Moreover, it was observed that wheels’ sinkage and driving torques are significantly larger for dry sand than for the other investigated ground types.</p> </abstract>ARTICLEtrue Lasalle Based Dynamic Stabilization for Fixedwing Drones<abstract> <title style='display:none'>Abstract</title> <p>The market of Unmanned Aerial Vehicles (UAVs) for civil applications is extensively growing. Indeed, these airplanes are now widely used in applications such as data gathering, agriculture monitoring and rescue. The UAVs are required to track a fixed or moving object; thus, tracking control algorithms that ensure the system stability and that have a quick time response must be developed. This paper tackles the problem of supervising a fixed target using a fixed wing UAV flying at a constant altitude and a constant speed. For that purpose, three control algorithms were developed. In all of the algorithms, the UAV is expected to hover around the target in a circular trajectory. Moreover, the three approaches are based upon a Lyapunov-LaSalle stabilization method. The first tracking algorithm ensures that the UAV circles around the target. However, the path that the UAV follows in order to join this pattern is not studied. In the second and third approach, two different techniques that allow the UAV to intercept its final circular pattern in the quickest possible time and thus follow the tangent to the circular pattern are presented. Simulation results that show and compare the performances of the proposed methods are presented.</p> </abstract>ARTICLEtrue Shuffled Frog Leaping Algorithm for Optimal Allocation of Power Quality Monitors in Unbalanced Distribution System<abstract> <title style='display:none'>Abstract</title> <p>This paper deals with optimal detection of number and best locations of power quality monitors (PQMs) in an unbalanced distribution network based on the monitor reach area concept. The proposed model uses binary string, representing the installation mode of PQMs (Yes or No) in each bus of the network. In this paper, the binary version of shuffled frog-leaping algorithm (BSFLA), because of having the ability to improve the search capability with a fast convergence rate, is utilized for the optimization process. The overall cost function is formulated to optimize the two indices, which are the monitor overlapping index and sag severity index. The only optimization constraint in this problem is that the number of monitors that can detect voltage sags due to a fault at a specific bus must not be zero. In this study, DIGSILENT software is utilized for fault analysis while the optimization problem is handled by the BSFLA. To verify the proposed algorithm, the IEEE 34 Bus unbalanced distribution network is considered as a case study and results are compared to similar investigations so as to illustrate the effectiveness of the proposed algorithm.</p> </abstract>ARTICLEtrue Robust Model for Stability and H∞ Analysis for Interconnected Embedded Systems<abstract> <title style='display:none'>Abstract</title> <p>This paper presents a novel approach to analyzing the robust stability of interconnected embedded systems. The paper starts by discussing the challenges associated with designing stable and robust embedded systems, particularly in the context of interconnected systems. The proposed approach combines the H∞ control theory with a new model for interconnected embedded systems, which takes into account the effects of communication delays and data losses. The paper provides a detailed mathematical analysis of the new model and presents several theorems and proofs related to its stability. The effectiveness of the proposed approach is demonstrated through several practical examples, including a networked control system and a distributed sensor network. The paper also discusses the limitations of the proposed approach and suggests several directions for future research. The proposed filter design method establishes a sufficient condition for the asymptotic stability of the error system and the satisfaction of a predefined H∞ performance index for time-invariant bounded uncertain parameters. This is achieved through the use of the strict linear matrix inequalities (LMI) approach and projection lemma. The design is formulated in terms of linear matrix inequalities (LMI). Numerical examples are provided to demonstrate the effectiveness of the proposed filter design methods.</p> </abstract>ARTICLEtrue Visual Assistant Using Yolo and SSD for Visually-Impaired Persons<abstract> <title style='display:none'>Abstract</title> <p>Artificial Intelligence has been touted as the next big thing that is capable of altering the current landscape of the technological domain. Through the use of Artificial Intelligence and Machine Learning, pioneering work has been undertaken in the area of Visual and Object Detection. In this paper, we undertake the analysis of a Visual Assistant Application for Guiding Visually-Impaired Individuals. With recent breakthroughs in computer vision and supervised learning models, the problem at hand has been reduced significantly to the point where new models are easier to build and implement than the already existing models. Different object detection models exist now that provide object tracking and detection with great accuracy. These techniques have been widely used in automating detection tasks in different areas. A few newly discovered detection approaches, such as the YOLO (You Only Look Once) and SSD (Single Shot Detector) approaches, have proved to be consistent and quite accurate at detecting objects in real-time. This paper attempts to utilize the combination of these state-of-the-art, realtime object detection techniques to develop a good base model. This paper also implements a ’Visual Assistant’ for visually impaired people. The results obtained are improved and superior compared to existing algorithms.</p> </abstract>ARTICLEtrue Network Optimization Using Frame Period with Channel Allocation Techniques<abstract> <title style='display:none'>Abstract</title> <p>Internet connectivity in WiMAX networks, along with various applications, is increasing rapidly, so the connectivity of internet and data transfer speed are always challenges for effective data transmission in wireless networks. Several factors affect the performance of networks. One important factor is to choose a suitable frame period for effective data transmissions. The performance of different frame periods with Round Robin and Strict Priority is evaluated in this work. A frame period in Round Robin performs better than a Strict Priority in terms of throughput, but a Strict Priority performs better in terms of drop rates. This paper also demonstrates that an effective frame period, when combined with a proper bandwidth allocation algorithm, yields better results. This work gives the analysis that Round Robin performs 83.8847% better while Strict Priority performs 86.0020% better than the earliest deadline first algorithms for 10 subscriber stations in terms of throughput. This work is helpful to researchers and industrialists for actual implementations in WiMAX networks.</p> </abstract>ARTICLEtrue Overview of Challenges in Detecting Patients’ Hazards During Robot-Aided Remote Home Motor Rehabilitation<abstract> <title style='display:none'>Abstract</title> <p>Minimally-supervised home rehabilitation has become an arising technological trend due to the shortages in medical staff. Implementing such requires providing advanced tools for automatic real-time safety monitoring. The paper presents an approach to designing the mentioned safety system based on measurements and modelling the interface between a patient’s musculoskeletal system and a rehabilitation device. The content covers the segmentation of patients regarding their health conditions and assigns them suitable measurement techniques. The defined groups are described by the hazards with which they are most endangered and their causes. Each case is correlated with the appropriate data type that may be used to detect potential risk. Moreover, a concept of using presented knowledge for tracking the safety of bones and soft tissues according to the biomechanical standards is included. The paper forms a set of guidelines for designing safety systems based on measurements for robot-aided home kinesiotherapy. It can be used to select an appropriate approach regarding a specific case; which will decrease costs and increase the accuracy of the designed tools.</p> </abstract>ARTICLEtrue State Observer Based Robust Feedback Linearization Control Applied to an Industrial CSTR<abstract> <title style='display:none'>Abstract</title> <p>In the chemical and petrochemical industry, the Continuous Stirred Tank Reactors (CSTR) are, without doubt, one of the most popular processes. From a control point of view, the mathematical model describing the temporal evolution of the CSTR has a strongly nonlinear crosscoupled character. Moreover, modeling errors such as external disturbances, neglected dynamics, and parameter variations or uncertainties make its control task a very difficult challenge. Even though this problem has been the subject of a wide number of control strategies, this article attempts to propose a viable, robust, nonlinear decoupling control scheme. The idea behind the proposed approach lies in the design of two nested control loops. The inner loop is responsible for the compensation of the nominal model nonlinear cross-coupled terms via static nonlinear feedback; whereas the outer loop, designed around an Extended State Observer (ESO) of which the additional state gathers the global effect of modeling errors, is charged to instantaneously estimate, and then to compensate the ESO extended state. This way, the CSTR complex dynamics are reduced to a series of decoupled linear subsystems easily controllable using a simple Proportional-Integral (PI) linear control to ensure the robust pursuit of reference signals respecting the desired performance. The presented control validation was performed numerically by an objective comparison to a classical PID controller. The obtained results clearly show the viability and the effectiveness of the proposed control strategy for dealing with such nonlinear, strongly crosscoupled plants subject to a wide range of disturbances despite the precision of their described mathematical model.</p> </abstract>ARTICLEtrue Transposition Algorithm Using Cache Oblivious<abstract> <title style='display:none'>Abstract</title> <p>The Parallel and Distributed Computing group belonging to the Integrated Technological Research Complex (CITI). has been engaged in the creation of general-purpose components that support the processing of large volumes of information that characterize the problems involved in parallel computing.</p> <p>Using the oblivious cache model, which works independently of the computer architecture, and the divide and conquer principle, an algorithm for matrix transposition is implemented to reduce the execution time of this algebraic operation. The algorithm ensures that most of the data content is loaded to the cache for fast processing, and makes the most of its stay in the cache to minimize missed reads and achieve greater speed.</p> <p>The work includes conclusions and statistical tests carried out from experiments on computers with different architectures, reflecting the superiority of the algorithm that uses oblivious cache from an order of matrix determined according to the characteristics of each PC.</p> </abstract>ARTICLEtrue and Robust Following of 3D Paths by a Holonomic Manipulator<abstract> <title style='display:none'>Abstract</title> <p>This paper addresses the problem of the following three-dimensional path by holonomic manipulator with parametric or structural uncertainty in the dynamics. Description of the manipulator relative to a desired threedimensional path was presented. The path is parameterized orthogonally to the Serret-Frenet frame, which is moving along the curve. The adaptive and robust control laws for a stationary manipulator which ensures realization of the task were specified. Theoretical considerations are supported by the results of computer simulations conducted for an RTR manipulator.</p> </abstract>ARTICLEtrue Inverse Kinematics for Serial Manipulators<abstract> <title style='display:none'>Abstract</title> <p>This paper is a practical guideline on how to analyze and evaluate the literature algorithms of singularity-robust inverse kinematics or to construct new ones. Additive, multiplicative, and based on the Singularity Value Decomposition (SVD) methods are examined to retrieve well-conditioning of a matrix to be inverted in the Newton algorithm of inverse kinematics. It is shown that singularity avoidance can be performed in two different, but equivalent, ways: either via properly modified manipulability matrix or not allowing the decrease of the minimal singular value below a given threshold. It is discussed which method can always be used and which can only be used when some pre-conditions are met. Selected methods are compared to with respect to the efficiency of coping with singularities based on a theoretical analysis as well as simulation results. Also, some questions important for mathematically and/or practically oriented roboticians are stated and answered.</p> </abstract>ARTICLEtrue of Curvilinear Parametrization Methods and Avoidance of Orthogonal Singularities in the Path Following Task<abstract> <title style='display:none'>Abstract</title> <p>In this paper applications of curvilinear parametrizations (Serret–Frenet, Bishop) in the path following task have been considered. The parametrizations allow one to derive manipulator’s equations with respect to a path. The full mathematical model of the path following task involves two groups of equations, i.e., the dynamics of the manipulator and the equations obtained from the parametrization method, connected in the cascaded system.</p> <p>Based on those relations two path following algorithms have been designed according to the backstepping integrator method (dedicated to the cascaded systems). Depending on the chosen parametrization method the algorithms differ in requirements and performance. In the paper an in-depth analysis comparing features of both considered methods has been presented.</p> <p>The parametric description of a path requires projection of a robot on the path. In this article the orthogonal projection has been taken into account. It introduces a singularity in the robot description. We have proposed a new form of the orthogonal projection constraint which allows a robot to not only approach the path, but also move along it. This novelty design is an important enhancement of the algorithms used so far.</p> <p>The problem of partially known dynamic parameters of a robot has also been addressed. In this paper, we have shown how to apply an adaptive controller to the path following task.</p> <p>Theoretical considerations have been verified with a simulation study conducted for a holonomic stationary manipulator. Achieved results emphasized why it is strongly recommended to use the algorithm version with the orthogonal singularity outside the path. Moreover, the comparative analysis results may be used to select the best curvilinear parametrization method according to the considered task requirements.</p> </abstract>ARTICLEtrue Competitive Neural Network for Classification of Human Postures Based on Data from RGB-D Sensors<abstract> <title style='display:none'>Abstract</title> <p>The cognitive goal of this paper is to assess whether marker-less motion capture systems provide sufficient data to recognize human postures in the side view. The research goal is to develop a new posture classification method that allows for analysing human activities using data recorded by RGB-D sensors. The method is insensitive to recorded activity duration and gives satisfactory results for the sagittal plane. An improved competitive Neural Network (cNN) was used. The method of preprocessing the data is first discussed. Then, a method for classifying human postures is presented. Finally, classification quality using various distance metrics is assessed. The data sets covering the selection of human activities have been created. Postures typical for these activities have been identified using the classifying neural network. The classification quality obtained using the proposed cNN network and two other popular neural networks were compared. The results confirmed the advantage of cNN network. The developed method makes it possible to recognize human postures by observing movement in the sagittal plane.</p> </abstract>ARTICLEtrue Identification of Space Manipulator’s Flexible Joint<abstract> <title style='display:none'>Abstract</title> <p>A manipulator mounted on a satellite is often used to perform active debris removal missions. The space manipulator control system needs to take the dynamic model of the satellite-manipulator system into account because of the influence of the manipulator motion on the position and attitude of the satellite. Therefore, precise modeling of the space manipulator dynamics as well as parameter identification are needed to improve the credibility of the simulation tools. In this paper, we presented the identification of the flexible-joint space manipulator model based on dynamic equations of motion. Experiments were performed in an emulated microgravity environment using planar air bearings. The arbitrarily selected joint-space trajectory was performed by the manipulator’s control system. The experiments were repeated multiple times in order to analyze the identification method sensitivity. The identification is based on the Simulink SimMechanics model. Thus, the procedure can be used for any space manipulator without the need to obtain analytical relations for dynamic equations each time. Including joint flexibility and spring viscous damping in the dynamic model allowed it to reflect the experimental measurements better than the reference model could. Identified parameters of the flexible joint have values of the same magnitude as corresponding real system parameters.</p> </abstract>ARTICLEtrue Robot Programming Interface Based on RGB-D Perception and Neural Scene Understanding Modules<abstract> <title style='display:none'>Abstract</title> <p>In this paper, we propose a system for natural and intuitive interaction with the robot. Its purpose is to allow a person with no specialized knowledge or training in robot programming to program a robotic arm. We utilize data from the RGB-D camera to segment the scene and detect objects. We also estimate the configuration of the operator’s hand and the position of the visual marker to determine the intentions of the operator and the actions of the robot. To this end, we utilize trained neural networks and operations on the input point clouds. Also, voice commands are used to define or trigger the execution of the motion. Finally, we performed a set of experiments to show the properties of the proposed system.</p> </abstract>ARTICLEtrue Human Action/Interaction Classification in Sparse Image Sequences<abstract> <title style='display:none'>Abstract</title> <p>Research results on human activity classification in video are described, based on initial human skeleton estimation in selected video frames. Simple, homogeneous activities, limited to single person actions and two-person interactions, are considered. The initial skeleton data is estimated in selected video frames by software tools, like “OpenPose” or “HRNet”. Main contributions of presented work are the steps of “skeleton tracking and correcting” and “relational feature extraction”. It is shown that this feature engineering step significantly increases the classification accuracy compared to the case of raw skeleton data processing. Regarding the final neural network encoder-classifier, two different architectures are designed and evaluated. The first solution is a lightweight multilayer perceptron (MLP) network, implementing the idea of a “mixture of pose experts”. Several pose classifiers (experts) are trained on different time periods (snapshots) of visual actions/interactions, while the final classification is a time-related pooling of weighted expert classifications. All pose experts share a common deep encoding network. The second (middle weight) solution is based on a “long short-term memory” (LSTM) network. Both solutions are trained and tested on the well-known NTU RGB+D dataset, although only 2D data are used. Our results show comparable performance with some of the best reported LSTM-, Graph Convolutional Network-(GCN), and Convolutional Neural Network-based classifiers for this dataset. We conclude that, by reducing the noise of skeleton data, highly successful lightweight- and midweight-models for the recognition of brief activities in image sequences can be achieved.</p> </abstract>ARTICLEtrue of the Spherical Fuzzy Dematel Model for Assessing the Drone Apps Issues<abstract> <title style='display:none'>Abstract</title> <p>During the past few years, the number of drones (unmanned aerial vehicles, or UAVs) manufactured and purchased has risen dramatically. It is predicted that it will continue to spread, making its use inevitable in all walks of life. Drone apps are therefore expected to overrun the app stores in the near future. The UAV’s software is not being studied/researched despite several active research and studies being carried out in the UAV’s hardware field. A large-scale empirical analysis of Google Play Store Platform apps connected to drones is being done in this direction. There are, however, a number of challenges with drone apps because of the lack of formal and specialized app development procedures. In this paper, eleven drone app issues have been identified. Then we applied the DEMATEL (Decision Making Trial and Evaluation Laboratory) method to analyze the drone app issues (DIs) and divide these issues into cause and effect groups. First, multiple experts assess the direct relationships between influential issues in drone apps. The evaluation results are presented in spherical fuzzy numbers (SFN). Secondly, we convert the linguistic terms into SFN. Thirdly, based on DEMATEL, the cause-effect classifications of issues are obtained. Finally, the issues in the cause category are identified as DI’s in drone apps. The outcome of the research is compared with the other variants of DEMATEL, like rough-Z-numberbased DEMATEL and spherical fuzzy number, and the comparative results suggest that spherical fuzzy DEMATEL is the most fitting method to analyze the interrelationship of different issues in drone apps. The findings revealed that highest influenced values feature request (DI<sub>9</sub>) 3.12, Customer support (DI<sub>6</sub>) 2.91, Connection/Sync ((DI<sub>4</sub>) 2./72, Cellular Data Usage ((DI<sub>3</sub>) 2.51, Battery (DI<sub>2</sub>) 2.31, Advertisements ((DI<sub>1</sub>) – 0.3, Cost (DI<sub>5</sub>) – 0.5, Additional cost (D<sub>11</sub>) – 0.5, Device Compatibility (DI<sub>7</sub>) – 0.96, and Functional Error (DI<sub>10</sub>) – 1.2. The outcome of this work definitely assists the software industry in the successful identification of the critical issues where professionals and project managers could really focus.</p> </abstract>ARTICLEtrue Heavymoving Average Distances In Sales Forecasting<abstract> <title style='display:none'>Abstract</title> <p>This paper presents a new aggregation operator technique that uses the ordered weighted average (OWA), heavy aggregation operators, Hamming distance, and moving averages. This approach is called heavy ordered weighted moving average distance (HOWMAD). The main advantage of this operator is that it can use the characteristics of the HOWMA operator to under-or overestimate the results according to the expectations and the knowledge of the future scenarios, analyze the historical data of the moving average, and compare the different alternatives with the ideal results of the distance measures. Some of the main families and specific cases using generalized and quasi-arithmetic means are presented, such as the generalized heavy moving average distance and a generalized HOWMAD. This study develops an application of this operator in forecasting the sales growth rate for a commercial company. We find that it is possible to determine whether the company’s objectives can be achieved or must be reevaluated in response to the actual situation and future expectations of the enterprise.</p> </abstract>ARTICLEtrue on the Study of Alzheimer’s Disease Through Artificial Intelligence Techniques<abstract> <title style='display:none'>Abstract</title> <p>Alzheimer’s disease is the most common form of dementia that can cause a brain neurological disorder with progressive memory loss as a result of brain cell damage. Prevention and treatment of disease is a key challenge in today’s aging society. Accurate diagnosis of Alzheimer’s disease plays an important role in patient management, especially in the early stages of the disease, because awareness of risk allows patients to undergo preventive measures even before irreversible brain damage occurs. Over the years, techniques such as statistical modeling or machine learning algorithms have been used to improve understanding of this condition. The objective of the work is the study of the methods of detection and progression of Alzheimer’s disease through artificial intelligence techniques that have been proposed in the last three years.</p> <p>The methodology used was based on the search, selection, review, and analysis of the state of the art and the most current articles published on the subject. The most representative works were analyzed, which allowed proposing a taxonomic classification of the studied methods and on this basis a possible solution strategy was proposed within the framework of the project developed by the Cuban Center for Neurosciences based on the conditions more convenient in terms of cost and effectiveness and the most current trends based on the use of artificial intelligence techniques.</p> </abstract>ARTICLEtrue Model of Photovoltaic System Adapted By a Digital Mppt Control and Radiation Predictions Using Deep Learning in Morocco Agricultural Sector<abstract> <title style='display:none'>Abstract</title> <p>Solar energy is an essential factor in Moroccan sustainable development, especially in solar pumping in the agricultural sector. It is therefore difficult to dissociate the energy system of a society from its economic development and social development. Solar radiation prediction is useful in giving us a global overview on maintaining the integrity of solar systems. Access to database use makes this process more flexible. Solar forecasts can be generated using various available data sources. There are two major pillars of this data: the exploitation of historical solar radiation data, and the exploitation of other meteorological factors. On the other hand, the choice of data can have an impact on the choice of the model and the approach employed. In this paper we suggest an idea that aims to monitor in real time the situation of solar radiation in Morocco, using Long Short-Term Memory for deep learning models compared with Artificial Neural Networks and Deep Neural Networks to predict the solar radiation with regard to solar pumping in the Moroccan agricultural sector.</p> </abstract>ARTICLEtrue