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Asian Control Conference

作者： Seyyed Hamid R. Ebrahimi Motlagh Hadi Moradi Hamidreza Pouretemad Advanced Robotics and Intelligent Systems Laboratory Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran ARIS and CIPCE School of ECE College of Engineering University of Tehran Iran Shahid Beheshti University Tehran Tehran IR

ISBN: (纸本)9781467357661

Early detection of autism is crucial for successfully dealing with it and reduce/eliminate its effects. In other words, early treatment can make a big difference in the lives of many children with this disorder. Consequently, in this study the pattern recognition algorithms are used to determine the unique features of the voice of autistic children to distinguish between the autistic children and normal children between ages 2 and 3. These descriptors extract various audio features such as temporal features, energy features, harmonic features, perceptual and spectral features. Two feature selection methods are used and the results are compared. One method is based on comparing the effect of using all of a group features together and another method compares the effect of using features one by one. The selected features are used to classify selected children into autistic and non-autistic ones. The results show 96.17 percent accuracy. After feature selection, we classified data using S.V.M classifier for recognizing two types of input data.

关键词： Autism Feature extraction Mel frequency cepstral coefficient Educational institutions Harmonic analysis Accuracy Motion pictures

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Finding Objects with Segmentation Strategy based Multi Robot Exploration in Unknown Environment

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Procedia - Social and Behavioral Sciences 2013年 97卷 580-586页

作者： Reza Arezoumand Syamsiah Mashohor Mohammad Hamiruce Marhaban Intelligent System and Robotics Laboratory Institute of Advanced Technology Universiti Putra Malaysia 43400 Serdang Selangor Malaysia Department of Computer & Communication Systems Faculty of Engineering Universiti Putra Malaysia 43400 Serdang Selangor Malaysia Department of Electrical and Electronic Engineering University Putra Malaysia 43400 Serdang Selangor Malaysia

In this paper we address exploration algorithm in flat experimental environment with colored objects for multi robots system. The aim of exploration in unknown environment is finding target points like mine detection in outdoor environment without any positioning device. Two algorithms were investigated in this paper one is frontier based random search algorithm and the second is efficient algorithm based on segmentation strategy. To improve efficiency, each robot had to go to different regions to avoid cumulating robots in one region. Constructed maps for all four regions could be shared and navigation could be done more effectively. For constructing map robot can use on built range finder sensor or using vision based systems. Also the algorithm using segmentation strategy is using frontier base algorithm for exploring divided area. Both algorithm implemented and analyzed in Player/Stage simulation. The result was compared and showed the efficiency of the designed algorithm based segmentation strategy. In simulation this algorithm is tested with different number of robots to achieve better view of efficiency for proposed algorithm in different type of environment like harsh environment as possibility of losing some robots.

关键词： Multi-robot exploration Flocking Exploration ratio Trajectory prediction

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Joint ASV/AUV range-based formation control: Theory and experimental results

Joint ASV/AUV range-based formation control: Theory and expe...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jorge M. Soares A. Pedro Aguiar António M. Pascoal Alcherio Martinoli Laboratory of Robotics and Systems in Engineering and Science Instituto SuperiorTécnico Technical University of Lisbon Lisboa Portugal Department of Electrical and Computer Engineering Faculty of Engineering University of Porto Porto Portugal

ISBN: (纸本)9781467356404

The use of groups of autonomous marine vehicles has enormous potential in numerous marine applications, perhaps the most relevant of which is the surveying and exploration of the oceans, still widely unknown and misunderstood. In many mission scenarios requiring the concerted operation of multiple marine vehicles carrying distinct, yet complementary sensor suites, relative positioning and formation control becomes mandatory. However, the constraints placed by the medium make it hard to both communicate and localize vehicles, even in relation to each other. In this paper, we deal with the challenging problem of keeping an autonomous underwater vehicle in a moving triangular formation with respect to 2 leader vehicles. We build upon our previous theoretical work on range-only formation control, which presents simple feedback laws to drive the controlled vehicle to its intended position in the formation using only ranges obtained to the leading vehicles with no knowledge of the formation path. We then introduce the real-world constraints associated with the use of autonomous underwater vehicles, especially the low frequency characteristics of acoustic ranging and its unreliability. We discuss the required changes to implement the solution in our vehicles, and provide simulation results using a full dynamic and communication model. Finally, we present the results of real world trials using MEDUSA-class autonomous marine vehicles.

关键词： Vehicles Vehicle dynamics Acoustics Underwater vehicles Robots Distance measurement

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Method of SLAM with Kinect

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Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) 2013年第SUPPL.2期44卷 28-32页

作者： Li, Haiyang Li, Hongbo Lin, Ying Liu, Heping Yang, Dongfang School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing 100084 China

A method for Kinect sensor was presented based on SLAM (simultaneous localization and mapping) problem via inverse depth parameterization model, where the depth of features from Kinect was employed to improve the convergence of method. To further improve the accuracy and robustness, SURF (speed up robust features) feature detection operator was adopted to extract image features, and extended Kalman filter (EKF) was used to estimate the trajectory of camera and the position of features. Experimental results are given to demonstrate the effectiveness and applicability of the proposed method.

关键词： Extended Kalman filters

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CNN based power system transient stability margin and voltage stability index prediction

CNN based power system transient stability margin and voltag...

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IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG)

作者： Karthikeyan Balasubramaniam Ganesh Kumar Venayagamoorthy Neville Watson Real-Time Power and Intelligent Systems Laboratory Holcombe Department of Electrical & Computer Engineering Clemson University Clemson SC USA Department of Electrical Engineering University of Canterbury Christchurch New Zealand

Operators at electric grid control centers are faced with the task of making important decisions in real-time. With the plethora of data available it becomes important to extract information from the available data, based on which knowledge of system condition can be formed. This knowledge can then be used in decision making. Metrics such as transient stability margin (TSM) and voltage stability load index (VSLI) help in assessing the stability of the system. In this study, cellular neural network (CNN) based stability margin prediction system is developed in a distributed computing framework. The developed system not only extracts information from available data but also predicts the same, one step ahead of time. Moreover, the framework employed uses distributed computing and hence could be used on a large scale power system with a linear increase in computation time instead of an exponential increase. A reduced version of New Zealand's South Island power system is used as the test system to demonstrate the feasibility of CNNs for TSM and VSLI prediction.

关键词： Power system stability Generators Stability criteria Rotors Transient analysis

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Darwinian Robotic Swarms for exploration with minimal communication

Darwinian Robotic Swarms for exploration with minimal commun...

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Congress on Evolutionary Computation

作者： Micael S. Couceiro Rui P. Rocha Nuno M. F. Ferreira Patricia A. Vargas Institute of Systems and Robotics University of Coimbra Coimbra Portugal Department of Electrical Engineering Engineering Institute of Coimbra Robo Corporation Coimbra Portugal Robotics Laboratory School of Mathematical and Computer Science Heriot-Watt University Edinburgh UK

ISBN: (纸本)9781479904532

The Robotic Darwinian Particle Swarm Optimization (RDPSO) recently introduced in the literature has the ability to dynamically partition the whole population of robots based on simple “punish-reward” rules. Although this evolutionary algorithm enables the reduction of the amount of required information exchange among robots, a further analysis on the communication complexity of the RDPSO needs to be carried out so as to evaluate its scalability. This paper analyses the architecture of the RDPSO communication system, thus describing the dynamics of the communication data packet structure shared between teammates. Moreover, a set of simple communication rules is also proposed in order to reduce the communication overhead within swarms of robots. Experimental results with teams of 15 real robots show that the proposed methodology reduces the communication overhead, thus improving the scalability and applicability of the RDPSO algorithm.

关键词： Robot kinematics Robot sensing systems Mobile ad hoc networks Complexity theory Spread spectrum communication Force

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Power system controller design using multi-population PBIL

Power system controller design using multi-population PBIL

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IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG)

作者： Komla Agbenyo Folly Ganesh Kumar Venayagamoorthy Department of Electrical Engineering University of Cape Town Cape Town South Africa Real-Time Power and Intelligent Systems Laboratory Holcombe Department of Electrical & Computer Engineering Clemson University SC USA

The application of a multi-population based Population-Based Incremental Learning (PBIL) to power system controller design is presented in this paper. PBIL is a combination of evolutionary optimization and competitive learning derived from artificial neural networks. Single population PBIL has recently received increasing attention in various engineering fields due to its effectiveness., easy implementation and robustness. Despite these strengths., PBIL still suffers from issues of loss of diversity in the population. The use of multi-population is seen as one way of increasing the diversity in the population. The approach is applied to power system controller design. Simulations results show that the multi-population PBIL approach performs better than the standard PBIL and is as effective as PBIL where adaptive learning is used.

关键词： Vectors Sociology Statistics Standards Power system stability Optimization Control systems

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Toward a Hybrid Approach to Generate Software Product Line Portfolios

Toward a Hybrid Approach to Generate Software Product Line P...

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IEEE Congress on Evolutionary Computation

作者： Jonathas Cruz Pedro Santos Neto Ricardo Britto Ricardo Rabelo Werney Ayala Thiago Soares Mauricio Mota Software Engineering and Industrial Informatics (EASII) Computer Science Department (DC) Federal University of Piaui (UFPI) LABoratory of Intelligent Robotics Automation and Systems (LABIRAS) State University of Piaui (UESPI)

ISBN: (纸本)9781479904532

Software Product Line (SPL) development is a new approach to software engineering that aims at the development of a whole range of products. One of the problems which hinders the adoption of that approach is related with the management of the products of the line. Additionally, the scope of a software product line is determined by the bounds of the capabilities provided by the collection of products in the product line. This introduces new challenges related to the scope problem. One of the main three different forms of scoping is the Product Portfolio Scoping (PPS). PPS aims at defining the products that should be developed as well as their key features. While this has an impact on the actual reuse opportunities, it is usually driven from marketing aspects. Defining a product portfolio by considering costumers satisfaction and cost aspects is a NP-hard problem. This work presents a hybrid approach, which combines fuzzy inference systems and the multi-objective metaheuristics NSGA-II to support product management by generating portfolios of products, based in segments of users and the development cost of the assets of the SPL. Fuzzy inference systems are used to generate development cost of an asset by using coupling, number of code lines and cyclomatic complexity and also to estimate the quality of the products generated by the optimization module of our approach. The NSGA-II metaheuristic is used to search for products minimizing the cost and maximizing the relevance of the candidate products. The results show that the proposed approach is effective in proposing the best products in terms of relevance and cost of the assets.

关键词： Portfolios Correlation Fuzzy logic Indexes Optimization Couplings Complexity theory

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A hybrid genetic algorithm-neural network for modeling of periodic nonlinearity in three-longitudinal-mode laser heterodyne interferometer

A hybrid genetic algorithm-neural network for modeling of pe...

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Iranian Conference on electrical engineering (ICEE)

作者： Saeed Olyaee Reza Ebrahimpur Somayeh Esfandeh Nano-photonics and Optoelectronics Research Laboratory (NORLab) and Brain and Intelligent Systems Research Laboratory Faculty of Electrical and Computer Engineering Shahid Rajaee Teacher Training University Tehran Iran

ISBN: (纸本)9781467356329

Laser heterodyne interferometer is a common nano-metrology system which is used for high-accuracy displacement measurements in industry. Measurement accuracy in this system is limited by the periodic nonlinearity error. In this paper, the nonlinearity error of the nano-metrology interferometric system based on three-longitudinal-mode laser heterodyne interferometer has been modeled by artificial neural network (ANN) and hybrid genetic algorithm-neural network (hybrid GA-ANN). The real code version of genetic algorithm (GA) is used. Genetic operators and parameters are set and designed accurately for optimizing the neural network. The results indicate that nonlinearity error can be effectively modeled by hybrid GA-ANN method and contains minimum mean square error (MSE) compared to the neural network.

关键词： Genetic algorithms Neural networks Training Measurement by laser beam Neurons Optical interferometry Laser modes

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An adaptive P300 model for controlling a humanoid robot with mind

An adaptive P300 model for controlling a humanoid robot with...

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IEEE International Conference on robotics and Biomimetics

作者： Mengfan Li Wei Li Jing Zhao Qinghao Meng Fuchun Sun Genshe Chen The Institute of Robotics and Autonomous Systems Tianjin University Tianjin China Department of Computer & Electrical Engineering and Computer Science California State University Bakersfield California USA the Institute of Robotics and Autonomous Systems Tianjin University Tianjin China Department of Computer Science and Technology Tsinghua University Beijing China The Intelligent Fusion Technology Inc. Germantown MD

ISBN: (纸本)9781479927456

This paper presents a P300 model for controlling a humanoid robot with mind, including an off-line phase with a fixed trial number for training the model and an on-line phase with an adaptive strategy for generating commands to the humanoid robot. Our control scheme includes a procedure of acquiring P300 signals, topographical distribution analysis of P300 signals, and a classification approach to identifying subjects' mental activities regarding robot-walking behavior. Our study shows that the adaptive model is fast and practical to control humanoid robot via brainwaves.

关键词： Adaptation models Humanoid robots Accuracy Context Brain modeling Testing

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