Search results for: robust navigation

Authors: Manlika Ratchagit

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This paper is concerned with robust mean square stability of uncertain stochastic switched discrete time-delay systems. The system to be considered is subject to interval time-varying delays, which allows the delay to be a fast time-varying function and the lower bound is not restricted to zero. Based on the discrete Lyapunov functional, a switching rule for the robust mean square stability for the uncertain stochastic discrete time-delay system is designed via linear matrix inequalities. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: robust mean square stability, discrete-time stochastic systems, hybrid systems, interval time-varying delays, Lyapunov functional, linear matrix inequalities

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Authors: Manlika Rajchakit

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This paper is concerned with robust mean square stability of uncertain stochastic switched discrete time-delay systems. The system to be considered is subject to interval time-varying delays, which allows the delay to be a fast time-varying function and the lower bound is not restricted to zero. Based on the discrete Lyapunov functional, a switching rule for the robust mean square stability for the uncertain stochastic discrete time-delay system is designed via linear matrix inequalities. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: robust mean square stability, discrete-time stochastic systems, hybrid systems, interval time-varying delays, lyapunov functional, linear matrix inequalities

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Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

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All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.

Keywords: currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features

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Authors: Elena Castillo-López, Raúl Pereda, Julio Manuel de Luis, Rubén Pérez, Felipe Piña

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Sediments are an important source of accumulation of toxic contaminants within the aquatic environment. Bioassays are a powerful tool for the study of sediments in relation to their toxicity, but they can be expensive. This article presents a methodology to estimate the main physical property of intertidal sediments in coastal zones: heavy metals concentration. This study, which was developed in the Bay of Santander (Spain), applies classical and robust statistic to CASI-2 hyperspectral images to estimate heavy metals presence and ecotoxicity (TOC). Simultaneous fieldwork (radiometric and chemical sampling) allowed an appropriate atmospheric correction to CASI-2 images.

Keywords: remote sensing, intertidal sediment, airborne sensors, heavy metals, eTOCoxicity, robust statistic, estimation

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Authors: Sandeep Reddy, Sonia Allan, Simon Coghlan, Paul Cooper

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Artificial Intelligence (AI) and its application in medicine has generated ample interest amongst policymakers and clinicians. Successes with AI in medical imaging interpretation and clinical decision support are paving the way for its incorporation into routine healthcare delivery. While there has been a focus on the development of ethical principles to guide its application in healthcare, challenges of this application go beyond what ethics principles can address thus requiring robust governance frameworks. Also, while ethical challenges of medical artificial intelligence are being discussed, the ethics of deploying AI in lower-income countries receive less attention than in other developed economies. This creates an imperative not only for sound ethical guidelines but also for robust governance frameworks to regulate AI in medicine around the world. In this article, we discuss what components need to be considered in developing these governance frameworks and who should lead this worldwide effort.

Keywords: artificial intelligence, global health, governance, ethics

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Authors: Wararit Panichkitkosolkul

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The unit root tests based on the robust estimator for the first-order autoregressive process are proposed and compared with the unit root tests based on the ordinary least squares (OLS) estimator. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of Type I error and powers of the unit root tests are estimated via Monte Carlo simulation. Simulation results show that all unit root tests can control the probability of Type I error for all situations. The empirical power of the unit root tests based on the robust estimator are higher than the unit root tests based on the OLS estimator.

Keywords: autoregressive, ordinary least squares, type i error, power of the test, Monte Carlo simulation

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Authors: Tran Gia Khanh, Dao Phuong Nam, Do Trong Tan, Nguyen Van Huong, Mai Xuan Sinh

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This work presents the problem of tube-based robust model predictive controller for a class of continuous-time systems in the presence of input disturbances. The main objective is to point out the state trajectory of closed system being maintained inside a sequence of tubes. An estimation of attraction region of the closed system is pointed out based on input state stability (ISS) theory and linearized model in each time interval. The theoretical analysis and simulation results demonstrate the performance of the proposed algorithm for a wheeled inverted pendulum system.

Keywords: input state stability (ISS), tube-based robust MPC, continuous-time nonlinear systems, wheeled inverted pendulum

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Authors: Resul Fikir

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Unmanned Aircraft Systems (UAS) become indispensable parts of modern airpower as force multiplier .One of the main advantages of UAS is long endurance. UAS have to take extra payloads to accomplish different missions but these payloads decrease endurance of aircraft because of increasing drug. There are continuing researches to increase the capability of UAS. There are some vertical thermal air currents, which can cause climb and increase endurance, in nature. Birds and gliders use thermals to gain altitude with no effort. UAS have wide wing which can use of thermals like birds and gliders. Thermal regions, which is area of 2-3 NM, exist all around the world. It is free and clean source. This study analyses if thermal regions can be adopted and implemented as an assistant tool for UAS route planning. First and second part of study will contain information about the thermal regions and current applications about UAS in aviation and climbing performance with a real example. Continuing parts will analyze the contribution of thermal regions to UAS endurance. Contribution is important because planning declaration of UAS navigation rules will be in 2015.

Keywords: unmanned aircraft systems, Air4All, thermals, gliders

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Authors: R. Rama Kishore, Sunesh

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Nowadays, robust and secure watermarking algorithm and its optimization have been need of the hour. A watermarking algorithm is presented to achieve the copy right protection of the owner based on visual cryptography, histogram shape property and entropy. In this, both host image and watermark are preprocessed. Host image is preprocessed by using Butterworth filter, and watermark is with visual cryptography. Applying visual cryptography on water mark generates two shares. One share is used for embedding the watermark, and the other one is used for solving any dispute with the aid of trusted authority. Usage of histogram shape makes the process more robust against geometric and signal processing attacks. The combination of visual cryptography, Butterworth filter, histogram, and entropy can make the algorithm more robust, imperceptible, and copy right protection of the owner.

Keywords: digital watermarking, visual cryptography, histogram, butter worth filter

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Authors: Sarah Odofin, Zhiwei Gao

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Operations and maintenance of wind turbine have received much attention by researcher due to rapid expansion of wind farms. This paper explores a novel fault diagnosis that is designed and optimized to be very sensitive to faults and robust to disturbances. The faults considered are the sensor faults of which the augmented observer is considered to enlarge faults and to be robust to disturbance. A qualitative model based analysis is proposed for early fault diagnosis to minimize downtime mostly caused by components breakdown and exploit productivity. Simulation results are computed validating the models provided which demonstrates system performance using practical application of fault type examples. The results demonstrate the effectiveness of the developed techniques investigated in a Matlab/Simulink environment.

Keywords: wind turbine, condition monitoring, genetic algorithm, fault diagnosis, augmented observer, disturbance robustness, fault estimation, sensor monitoring

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Authors: Belkacem Soundes, Guezouli Larbi

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This paper presents a robust and accurate method for text detection and localization over lecture videos. Frame regions are classified into text or background based on visual feature analysis. However, lecture video shows significant degradation mainly related to acquisition conditions, camera motion and environmental changes resulting in low quality videos. Hence, affecting feature extraction and description efficiency. Moreover, traditional text detection methods cannot be directly applied to lecture videos. Therefore, robust feature extraction methods dedicated to this specific video genre are required for robust and accurate text detection and extraction. Method consists of a three-step process: Slide region detection and segmentation; Feature extraction and non-text filtering. For robust and effective features extraction moment functions are used. Two distinct types of moments are used: orthogonal and non-orthogonal. For orthogonal Zernike Moments, both Pseudo Zernike moments are used, whereas for non-orthogonal ones Hu moments are used. Expressivity and description efficiency are given and discussed. Proposed approach shows that in general, orthogonal moments show high accuracy in comparison to the non-orthogonal one. Pseudo Zernike moments are more effective than Zernike with better computation time.

Keywords: text detection, text localization, lecture videos, pseudo zernike moments

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Authors: Abdulrahman S. Alturki, John S. Loomis

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This paper discusses a corner detection algorithm for camera calibration. Calibration is a necessary step in many computer vision and image processing applications. Robust corner detection for an image of a checkerboard is required to determine intrinsic and extrinsic parameters. In this paper, an algorithm for fully automatic and robust X-corner detection is presented. Checkerboard corner points are automatically found in each image without user interaction or any prior information regarding the number of rows or columns. The approach represents each X-corner with a quadratic fitting function. Using the fact that the X-corners are saddle points, the coefficients in the fitting function are used to identify each corner location. The automation of this process greatly simplifies calibration. Our method is robust against noise and different camera orientations. Experimental analysis shows the accuracy of our method using actual images acquired at different camera locations and orientations.

Keywords: camera calibration, corner detector, edge detector, saddle points

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Authors: Peter Sauer, Thomas Hinze, Petra Hofstedt

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To avoid obstacles in the surrounding environment and to navigate to a given target belong to the most important tasks for mobile robots. According to these tasks different data structures are suitable. To avoid near obstacles, occupancy grid maps are an ideal representation of the surroundings. For less fine grained tasks, such as navigating from one room to another in an apartment, pure grid maps are inappropriate. Grid maps are very detailed, calculating paths to navigate between rooms based on grid maps would take too long. Instead, graph-based data structures, so-called topologies, turn out to be a proper choice for such tasks. In this paper we present two methods to dynamically create topologies from grid maps. Both methods are based on non-uniform grid maps. The topologies are generated on-the-fly and can easily be modified to represent changes in the environment. This allows a hybrid approach to control mobile robots, where, depending on the situation and the current task, either the grid map or the generated topology may be used.

Keywords: robot navigation, occupancy grids, topological maps, dynamic map creation

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Authors: T. Sanches, K. Bousson

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As part of the development of a 4D autopilot system for unmanned aerial vehicles (UAVs), i.e. a time-dependent robust trajectory generation and control algorithm, this work addresses the problem of optimal path control based on the flight sensors data output that may be unreliable due to noise on data acquisition and/or transmission under certain circumstances. Although several filtering methods, such as the Kalman-Bucy filter or the Linear Quadratic Gaussian/Loop Transfer Recover Control (LQG/LTR), are available, the utter complexity of the control system, together with the robustness and reliability required of such a system on a UAV for airworthiness certifiable autonomous flight, required the development of a proper robust filter for a nonlinear system, as a way of further mitigate errors propagation to the control system and improve its ,performance. As such, a nonlinear algorithm based upon the LQG/LTR, is validated through computational simulation testing, is proposed on this paper.

Keywords: autonomous flight, LQG/LTR, nonlinear state estimator, robust flight control

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Authors: Dong Sang Yoo

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We consider nonlinear uncertain systems such that a priori information of the uncertainties is not available. For such systems, we assume that the upper bound of the uncertainties is represented as a Fredholm integral equation of the first kind and we propose an adaptation law that is capable of estimating the upper bound and design a continuous robust control which renders nonlinear uncertain systems ultimately bounded.

Keywords: adaptive control, estimation, Fredholm integral, uncertain system

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Authors: Yulong Wang, Yuan Yan Tang, Cuiming Zou, Lina Yang

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This paper presents a novel sparse representation method for robust pattern classification. Generalized orthogonal matching pursuit (GOMP) is a recently proposed efficient sparse representation technique. However, GOMP adopts the mean square error (MSE) criterion and assign the same weights to all measurements, including both severely and slightly corrupted ones. To reduce the limitation, we propose an information-theoretic GOMP (ITGOMP) method by exploiting the correntropy induced metric. The results show that ITGOMP can adaptively assign small weights on severely contaminated measurements and large weights on clean ones, respectively. An ITGOMP based classifier is further developed for robust pattern classification. The experiments on public real datasets demonstrate the efficacy of the proposed approach.

Keywords: correntropy induced metric, matching pursuit, pattern classification, sparse representation

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Authors: Mbadiwe S. Benyeogor, Oladayo O. Olakanmi, Kosisochukwu P. Nnoli, Olusegun I. Lawal, Eric JJ. Gratton

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For a robot or any vehicular system to navigate in off-road terrain, its driving mechanisms and the electro-software system must be capable of generating, controlling, and moderating sufficient mechanical power with precision. This paper proposes an autonomous robot with a gyro-stabilized active suspension system in form of a hybrid quadrupedal wheel drive mechanism. This system is to serve as a miniature model for demonstrating how off-road vehicles can be robotized into efficient terramechanical mobile platforms that are capable of self-balanced autonomous navigation and maneuvering on rough and uneven topographies. Results from tests and analysis show that the developed system performs as expected. Therefore, our model and control devices can be adapted to computerizing, automating, and upgrading the operation of unmanned ground vehicles for off-road navigation.

Keywords: active suspension, autonomous robots, edge computing, navigational sensors, terramechanics

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Authors: Khon Natalya, Kim Alla, Mukhitdinova Tansulu

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The aim of the research was to reveal the link between mental variables, such as spatial abilities, memory, intellect and professional experience of drivers. Participants were allocated within 4 groups: no experience, inexperienced, skilled and professionals (total 85 participants). Level of ability for spatial navigation and indicator of nonverbal memory grow along the process of accumulation of driving experience. At high levels of driving experience this tendency is especially noticeable. The professionals having personal achievements in driving (racing) differ from skilled drivers in better feeling of direction which is specific for them not just in a short-term situation of an experimental task, but in life-size perspective. The level of ability of mental rotation does not grow with growth of driving experience which confirms the multiple intelligence theory according to which spatial abilities represent specific, other than logical intelligence type of intellect. The link between spatial abilities, memory, intellect, and professional experience of drivers seems to be different relating spatial navigation or mental rotation as different kinds of spatial abilities.

Keywords: memory, spatial ability, intellect, drivers

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Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

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This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling

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Authors: David L. Olson, Stephen B. H. Bruder, Adam S. Watkins, Cleon E. Davis

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In global navigation satellite systems (GNSS), denied settings such as indoor environments, autonomous mobile robots are often limited to dead-reckoning navigation techniques to determine their position, velocity, and attitude (PVA). Localization is typically accomplished by employing an inertial measurement unit (IMU), which, while precise in nature, accumulates errors rapidly and severely degrades the localization solution. Standard sensor fusion methods, such as Kalman filtering, aim to fuse precise IMU measurements with accurate aiding sensors to establish a precise and accurate solution. In indoor environments, where GNSS and no other a priori information is known about the environment, effective sensor fusion is difficult to achieve, as accurate aiding sensor choices are sparse. However, an opportunity arises by employing a depth camera in the indoor environment. A depth camera can capture point clouds of the surrounding floors and walls. Extracting attitude from these surfaces can serve as an accurate aiding source, which directly combats errors that arise due to gyroscope imperfections. This configuration for sensor fusion leads to a dramatic reduction of PVA error compared to traditional aiding sensor configurations. This paper provides the theoretical basis for the depth camera aiding sensor method, initial expectations of performance benefit via simulation, and hardware implementation, thus verifying its veracity. Hardware implementation is performed on the Quanser Qbot 2™ mobile robot, with a Vector-Nav VN-200™ IMU and Kinect™ camera from Microsoft.

Keywords: autonomous mobile robotics, dead reckoning, depth camera, inertial navigation, Kalman filtering, localization, sensor fusion

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Authors: Long Cheng, Tong He, Iraj Mantegh, Wen-Fang Xie

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Path planning is essential for UAVs (Unmanned Aerial Vehicle) with autonomous navigation in unknown environments. In this paper, an adaptive probabilistic sampling algorithm is proposed for the GPS-denied environment, which can be utilized for autonomous navigation system of multiple UAVs in a dynamically-changing structured environment. This method can be used for Unmanned Aircraft Systems Traffic Management (UTM) solutions and in autonomous urban aerial mobility, where a number of platforms are expected to share the airspace. A path network is initially built off line based on available environment map, and on-board sensors systems on the flying UAVs are used for continuous situational awareness and to inform the changes in the path network. Simulation results based on MATLAB and Gazebo in different scenarios and algorithms performance measurement show the high efficiency and accuracy of the proposed technique in unknown environments.

Keywords: path planning, adaptive probabilistic sampling, obstacle avoidance, multiple unmanned aerial vehicles, unknown environments

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Authors: Fatma Romeh, Shiferaw Gurmu

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This paper examines the impact of female education on fertility, using the change in length of primary schooling in Egypt in 1988-89 as the source of exogenous variation in schooling. In particular, beginning in 1988, children had to attend primary school for only five years rather than six years. This change was applicable to all individuals born on or after October 1977. Using a nonparametric regression discontinuity approach, we compare education and fertility of women born just before and after October 1977. The results show that female education significantly reduces the number of children born per woman and delays the time until first birth. Applying a robust regression discontinuity approach, however, the impact of education on the number of children is no longer significant. The impact on the timing of first birth remained significant under the robust approach. Each year of female education postponed childbearing by three months, on average.

Keywords: Egypt, female education, fertility, robust regression discontinuity

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Authors: R. M. López-Gutiérrez, J. A. Michel-Macarty, H. Cervantes-De Avila, J. I. Nieto-Hipólito, C. Cruz-Hernández, L. Cardoza-Avendaño, S. Cortiant-Velez

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It is well know that mankind benefits from the application of robot control by virtual handlers in industrial environments. In recent years, great interest has emerged in the control of multiple robots in order to carry out collective tasks. One main trend is to copy the natural organization that some organisms have, such as, ants, bees, school of fish, birds’ migration, etc. Surely, this collaborative work, results in better outcomes than those obtain in an isolated or individual effort. This topic has a great drive because collaboration between several robots has the potential capability of carrying out more complicated tasks, doing so, with better efficiency, resiliency and fault tolerance, in cases such as: coordinate navigation towards a target, terrain exploration, and search-rescue operations. In this work, synchronization of multiple autonomous robots is shown over a variety of coupling topologies: star, ring, chain, and global. In all cases, collective synchronous behavior is achieved, in the complex networks formed with mobile robots. Nodes of these networks are modeled by a mass using Matlab to simulate them.

Keywords: robots, synchronization, bidirectional, coordinate navigation

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Authors: D. Vidhyaprakash, A. Elango

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In real-time applications, wheeled mobile robots are increasingly used and operated in extreme and diverse conditions traversing challenging surfaces such as a pitted, uneven terrain, natural flat, smooth terrain, as well as wet and dry surfaces. In order to accomplish such tasks, it is critical that the motion control functions without wheel slip and odometry error during the navigation of the two-wheeled mobile robot (WMR). Wheel slip and odometry error are disrupting factors on overall WMR performance in the form of deviation from desired trajectory, navigation, travel time and budgeted energy consumption. The wheeled mobile robot’s ability to operate at peak performance on various work surfaces without wheel slippage and odometry error is directly connected to four main parameters, which are the range of payload distribution, speed, wheel diameter, and wheel width. This paper analyses the effects of those parameters on overall performance and is concerned with determining the ideal range of parameters for optimum performance.

Keywords: wheeled mobile robot, terrain, wheel slippage, odometryerror, trajectory

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Authors: Mohammed H. Karim, Bestoon M. Faraj

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Introduction: This study aimed to compare the effectiveness of a Dynamic Navigation System (DNS) and a three-dimensional microscope in retrieving broken rotary NiTi files when using trepan burs and the extractor system. Materials and Methods: Thirty maxillary first bicuspids with sixty separate roots were split into two comparable groups based on a comprehensive Cone-Beam Computed Tomography (CBCT) analysis of the root length and curvature. After standardized access opening, glide paths, and patency attainment with the K file (sizes 10 and 15), the teeth were arranged on 3D models (three per quadrant, six per model). Subsequently, controlled-memory heat-treated NiTi rotary files (#25/0.04) were notched 4 mm from the tips and fractured at the apical third of the roots. The C-FR1 Endo file removal system was employed under both guidance to retrieve the fragments, and the success rate, canal aberration, treatment time and volumetric changes were measured. The statistical analysis was performed using IBM SPSS software at a significance level of 0.05. Results: The microscope-guided group had a higher success rate than the DNS guidance, but the difference was insignificant (p > 0.05). In addition, the microscope-guided drills resulted in a substantially lower proportion of canal aberration, required less time to retrieve the fragments and caused minimal change in the root canal volume (p < 0.05). Conclusion: Although dynamically guided trephining with the extractor can retrieve separated instruments, it is inferior to three-dimensional microscope guidance regarding treatment time, procedural errors, and volume change.

Keywords: separated instruments retrieval, dynamic navigation system, 3D video microscope, trephine burs, extractor

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Authors: Igor Faulmann, Arnaud Saj, Roland Maurer

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Spatial cognition consists in a plethora of high level cognitive abilities: among them, the ability to learn and to navigate in large scale environments is probably one of the most complex skills. Navigation is thought to rely on the ability to read a cognitive map, defined as an allocentric representation of ones environment. Those representations are of course intimately related to the two geometrical primitives of the environment: distance and direction. Also, many recent studies point to a predominant hippocampal and para-hippocampal role in spatial cognition, as well as in the more specific cluster of navigational skills. In a previous study in humans, we used a newly validated test assessing cognitive map processing by evaluating the ability to judge relative distances and directions: the CMRT (Cognitive Map Recall Test). This study identified in topographically disorientated patients (1) behavioral differences between the evaluation of distances and of directions, and (2) distinct causality patterns assessed via VLSM (i.e., distinct cerebral lesions cause distinct response patterns depending on the modality (distance vs direction questions). Thus, we hypothesized that: (1) if the CMRT really taps into the same resources as real navigation, there would be hippocampal, parahippocampal, and parietal activation, and (2) there exists underlying neuroanatomical and functional differences between the processing of this two modalities. Aiming toward a better understanding of the neuroanatomical correlates of the CMRT in humans, and more generally toward a better understanding of how the brain processes the cognitive map, we adapted the CMRT as an fMRI procedure. 23 healthy subjects (11 women, 12 men), all living in Geneva for at least 2 years, underwent the CMRT in fMRI. Results show, for distance and direction taken together, than the most active brain regions are the parietal, frontal and cerebellar parts. Additionally, and as expected, patterns of brain activation differ when comparing the two modalities. Furthermore, distance processing seems to rely more on parietal regions (compared to other brain regions in the same modality and also to direction). It is interesting to notice that no significant activity was observed in the hippocampal or parahippocampal areas. Direction processing seems to tap more into frontal and cerebellar brain regions (compared to other brain regions in the same modality and also to distance). Significant hippocampal and parahippocampal activity has been shown only in this modality. This results demonstrated a complex interaction of structures which are compatible with response patterns observed in other navigational tasks, thus showing that the CMRT taps at least partially into the same brain resources as real navigation. Additionally, differences between the processing of distances and directions leads to the conclusion that the human brain processes each modality distinctly. Further research should focus on the dynamics of this processing, allowing a clearer understanding between the two sub-processes.

Keywords: cognitive map, navigation, fMRI, spatial cognition

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Authors: Graziano Chesi

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The topological entropy plays a key role in linear dynamical systems, allowing one to establish the existence of stabilizing feedback controllers for linear systems in the presence of communications constraints. This paper addresses the determination of a robust value of the topological entropy in nonlinear dynamical systems, specifically the largest value of the topological entropy over all linearized models in a region of interest of the state space. It is shown that a sufficient condition for establishing upper bounds of the sought robust value of the topological entropy can be given in terms of a semidefinite program (SDP), which belongs to the class of convex optimization problems.

Keywords: non-linear system, communication constraint, topological entropy

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Authors: Abdolsalam Ghaderi

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In this paper, the single-depot capacitated location-routing problem under uncertainty is presented. The problem aims to find the optimal location of a single depot and the routing of vehicles to serve the customers when the parameters may change under different circumstances. This problem has many applications, especially in the area of supply chain management and distribution systems. To get closer to real-world situations, travel time of vehicles, the fixed cost of vehicles usage and customers’ demand are considered as a source of uncertainty. A combined approach including robust optimization and stochastic programming was presented to deal with the uncertainty in the problem at hand. For this purpose, a mixed integer programming model is developed and a heuristic algorithm based on Variable Neighborhood Search(VNS) is presented to solve the model. Finally, the computational results are presented and future research directions are discussed.

Keywords: location-routing problem, robust optimization, stochastic programming, variable neighborhood search

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Authors: Roya Ahmadi Ahangar, Hamid Madadyari

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The seeker optimization algorithm (SOA) is increasingly gaining popularity among the researchers society due to its effectiveness in solving some real-world optimization problems. This paper provides the load-frequency control method based on the SOA for removing oscillations in the power system. A three-zone power system includes a thermal zone, a hydraulic zone and a wind zone equipped with robust proportional-integral-differential (PID) controllers. The result of simulation indicates that load-frequency changes in the wind zone for the multi-zone system are damped in a short period of time. Meanwhile, in the oscillation period, the oscillations amplitude is not significant. The result of simulation emphasizes that the PID controller designed using the seeker optimization algorithm has a robust function and a better performance for oscillations damping compared to the traditional PID controller. The proposed controller’s performance has been compared to the performance of PID controller regulated with Particle Swarm Optimization (PSO) and. Genetic Algorithm (GA) and Artificial Bee Colony (ABC) algorithms in order to show the superior capability of the proposed SOA in regulating the PID controller. The simulation results emphasize the better performance of the optimized PID controller based on SOA compared to the PID controller optimized with PSO, GA and ABC algorithms.

Keywords: load-frequency control, multi zone, robust PID controller, wind generation

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Authors: Pierre F. Gerard, Frederic F. Leymarie, William Latham

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Architects have developed a series of objective evaluations, using spatial analysis tools such as Isovist, that show how certain spatial qualities are beneficial to specific human activities hosted in the built environments. In return, they can build more adapted environments by tuning those spatial qualities in their design. In parallel, virtual reality technologies have been developed by engineers with the dream of creating a system that immerses users in a new form of spatial experiences. They already have demonstrated a useful range of benefits not only in simulating critical events to assist people in acquiring new skills, but also to enhance memory retention, to name just a few. This paper investigates the effects of two spatial qualities, openness, and complexity, on cognitive performance within immersive virtual environments. Isovist measure is used to design a series of room settings with different levels of each spatial qualities. In an empirical study, each room was then used by every participant to solve a navigational puzzle game and give a rating of their spatial experience. They were then asked to fill in a questionnaire before solving the visual-spatial memory quiz, which addressed how well they remembered the different rooms. Findings suggest that those spatial qualities have an effect on some of the measures, including navigation performance and memory retention. In particular, there is an order effect for the navigation puzzle game. Participants tended to spend a longer time in the complex room settings. Moreover, there is an interaction effect while with more open settings, participants tended to perform better when in a simple setting; however, with more closed settings, participants tended to perform better in a more complex setting. For the visual-spatial memory quiz, participants performed significantly better within the more open rooms. We believe this is a first step in using virtual environments to enhance participant cognitive performances through better use of specific spatial qualities.

Keywords: architecture, navigation, spatial cognition, virtual reality

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