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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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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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Cooperative AUV Motion Planning using Terrain Information

Cooperative AUV Motion Planning using Terrain Information

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Oceans 2013 - Norway

作者： Andreas J. Hausler Alessandro Saccon Antonio M. Pascoal John Hauser A. Pedro Aguiar Laboratory of Robotics and Systems in Science and Engineering Instituto Superior Tecnico Department of Mechanical Engineering Eindhoven University of Technology Electrical Computer and Energy Engineering Department University of Colorado at Boulder Faculdade de Engenharia University of Porto

ISBN: (纸本)9781479900022

There is widespread interest in the deployment of fleets of marine robots with the potential to roam the oceans freely and collect data at an unprecedented scale. This calls for the development of efficient algorithms for multiple vehicle motion planning that can take directly into account the capabilities of each vehicle as well as the environmental conditions and lend themselves to seamless integration with control and navigation systems. The latter connection is for the most part eschewed in the literature, in spite of the obvious fact that in order for the vehicles to execute the planned motions they must at a later stage navigate with great accuracy and follow the trajectories using control algorithms that take explicitly into account the dynamical constraints of the vehicles involved. Among the methods available for underwater vehicle navigation, terrain-based techniques have recently come to the fore. These techniques avoid the use of overly expensive inertial-like motion sensor units and hold considerable promise for the development of a new breed of affordable long range navigation systems. Motivated by these considerations, we tackle in the present paper the problem of multiple vehicle motion planning by taking explicitly into consideration inter-vehicle collision avoidance, together with a number of criteria that may include simultaneous times of arrival at assigned target points, energy minimization, acoustic communication constraints, and the maximization of terrain information along the vehicle paths (as measured by some appropriate criterion) for terrain-based navigation purposes.

关键词： vehicle motion planning Collision avoidance terrains Autonomous underwater vehicles Data Collection Methods Navigation systems computer algorithms

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Incommensurate order fractional optimal control: Application to treatment of psychiatric disorders

Incommensurate order fractional optimal control: Application...

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Iranian Conference on electrical engineering (ICEE)

作者： S. S. Tabatabaei M. J. Yazdanpanah M. S. Tavazoei Department of Electrical Engineering Amirkabir University of Technology Tehran Iran Advanced Control Systems Laboratory Control and Intelligent Processing Center of Excellence School of Electrical and Computer Tehran Iran Electrical Engineering Department Sharif University of Technology Tehran Iran

ISBN: (纸本)9781467356329

The main point of this paper is to present a time domain strategy for drug dosage to treat psychiatric disorders. A time domain model of emotion is obtained from an extension of a recently developed fractional nonlinear dynamic model of happiness. First, the Fractional Optimal Control law for incommensurate multi state systems is obtained. It will be then applied as an optimal drug administration procedure in the line of psychiatric disorders treatment. Results of this paper show that optimal control scheme is a proper approach to face the difficulties of analysis and control the incommensurate systems. It can be also clearly seen from the simulation results that this approach is very effective in the case that control methods are used as treatment techniques.

关键词： Mathematical model Drugs Optimal control Numerical models Differential equations Equations

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Quantitative human and robot motion comparison for enabling assistive device evaluation

Quantitative human and robot motion comparison for enabling ...

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IEEE-RAS International Conference on Humanoid Robots

作者： Dana Kulić Muhammad Choudry Gentiane Venture Kanako Miura Eiichi Yoshida Electrical and Computer Engineering Department University of Waterloo Canada Department of Mechanical Systems Engineering Tokyo University of Agriculture and Technology Tokyo Japan CNRS-AIST JRL (Joint Robotics Laboratory) AIST Tsukuba Japan

A promising new application area for humanoid robots is in the area of assistive device testing. Humanoid robots can facilitate the experimental evaluation of assistive devices by providing repeatable, measurable, human-like motion while removing the difficulties and potential safety hazards associated with human trials. To ensure that the humanoid robot is providing a valid test platform, the robot must move in a similar way as a human while wearing the assistive device. This challenge is made difficult due to the inherent variability in human motion. In this paper, we propose an approach for a quantitative comparison between human and robot motion that identifies both the difference magnitude and the difference location, and explicitly handles both spatial and temporal variability of human motion. The proposed approach is demonstrated on data from robot gait and sagittal plane lifting.

关键词： Hidden Markov models Joints Assistive devices Humanoid robots Robot motion Computational modeling

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Real-time navigation for a humanoid robot using particle filter

Real-time navigation for a humanoid robot using particle fil...

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2nd International Conference on engineering and Technology Innovation 2012, ICETI 2012

作者： Baltes, Jacky Cheng, Chi Tai Lau, Meng Cheng Espínola, Andrés Autonomous Agents Lab Department of Computer Science University of Manitoba Winnipeg MB R3T 2N2 Canada Department of Electrical Engineering Tamkang University Tamsui Dist. New Taipei City 25137 Taiwan Mobile Robotics and Automated Systems Laboratory Universidad La Salle Benjamin Franklin 47 Mexico DF Mexico

ISBN: (纸本)9783037856123

This paper presents a practical real-time visual navigation system, including a vision system, a particle filter (PF) based localization system, and a path planning system, for humanoid robots in an indoor environment. A neural network (NN) converter system is used to solve the image distortion problem. The monocular vision system detects objects of interest in the scene, calculating their position in the image, and converting the position in the image to real world coordinates. The PF localization system estimates the current position by the robot's motion model and corrects the estimated position by using feedback from the data gathered by the vision system. The path planning system determines the next motion based on the result of the localization system. This paper uses a tree-like path planning method which not only guides the robot to the destination but also avoids obstacles at the same time. The navigation method allows a user to assign several different target destinations to the robot simultaneously. The proposed method is implemented on a humanoid robot "ROBOTIS DARwIn-OP", an open platform humanoid robot. The effectiveness of the system is demonstrated in an empirical evaluation. © (2013) Trans Tech Publications, Switzerland.

关键词： Bandpass filters

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A manually-actuated MRI compatible robotic manipulator for image-guided interventions

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Physica Medica 2014年 30卷 e55-e56页

作者： Eftychios G. Christoforou Christoforos Keroglou Andrew Webb Nikolaos V. Tsekos Ioannis Seimenis KIOS Research Center for Intelligent Systems and Networks University of Cyprus Cyprus Department of Electrical and Computer Engineering University of Cyprus Cyprus C.J. Gorter Center for High Field MRI Leiden University Medical Center Leiden Netherlands Medical Robotics Laboratory University of Houston Houston TX USA Med. Physics Lab Medical School Democritus University of Thrace Alexandroupolis Greece

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A positive tensions PID controller for a planar cable robot: An experimental study

A positive tensions PID controller for a planar cable robot:...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Mohammad A. Khosravi Hamid D. Taghirad Reza Oftadeh Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence (ICCE) Faculty of Electrical and Computer Engineering K. N. Toosi University of Technology Tehran Iran Intelligent Hydraulics and Automation Department (lHA) Tampere University of Technology Finland

In this paper design and control of planar cable-driven parallel robots are studied in an experimental prospective. Since in this class of manipulators, cable tensionability conditions must be met, feedback control of such robots becomes more challenging than for conventional robots. To meet these conditions, internal force control structure is introduced and used in addition to a PID control scheme to ensure that all cables remain in tension. A robust PID controller is proposed for partial knowledge of the robot, to keep the tracking errors bounded. Finally, the effectiveness of the proposed control algorithm is examined through experiments on K.N. Toosi planar cable-driven robot and it is shown that the proposed control structure is able to provide suitable performance in practice.

关键词： PD control Assembly Logic gates Servomotors Force

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COMPRESSIVE SENSING-BASED IMAGE DENOISING USING ADAPTIVE MULTIPLE SAMPLING AND OPTIMAL ERROR TOLERANCE

COMPRESSIVE SENSING-BASED IMAGE DENOISING USING ADAPTIVE MUL...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Wonseok Kang Eunsung Lee Eunjung Chea Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Seoul Chung-Ang University Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL 60208 USA

ISBN: (纸本)9781479903573

In this paper, we present a compressive sensing-based image denoising algorithm using spatially adaptive image representation and estimation of optimal error tolerance based on sparse signal analysis. The proposed method performs block-based multiple compressive sampling after decomposing the sparse signal into feature and non-feature regions using simple statistical analysis. For minimization of recovery error and number of iterations, the modified OMP method estimates the optimal error tolerance using the average variance in the recovery step. Experimental results demonstrate that the proposed denoising algorithm better removes noise without undesired artifacts than existing state-of-the-art methods in terms of both objective (PSNR/SSIM) and subjective measures. Processing time of the proposed method is 5 to 10 times faster than the standard OMP-based method.

关键词： Tolerances physiologic tolerance Sampling system recovery image denoising image representation images Signal analysis Statistical analysis Statistical methods image denoising algorithm

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An Automatic Electroencephalography Blinking Artefact Detection and Removal Method Based on Template Matching and Ensemble Empirical Mode Decomposition

An Automatic Electroencephalography Blinking Artefact Detect...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Paschalis A. Bizopoulos Tarik Al-Ani Dimitrios G. Tsalikakis Alexandros T. Tzallas Dimitrios D. Koutsouris Dimitrios I. Fotiadis Department Informatique et Telecommunication ESIEE-Paris LISV-Universite de Versailles Saint-Quentin-en-Yvelines Department of Informatics and Telecommunications Engineering University of Western Macedonia Unit of Medical Technology and Intelligent Information Systems Biomedical Engineering Laboratory School of Electrical and Computer Engineering National Technical University of Athens (NTUA) Unit of Medical Technology and Intelligent Information Systems Faculty of Material Science and Engineering University of Ioannina

ISBN: (纸本)9781457702150

Electrooculographic (EOG) artefacts are one of the most common causes of Electroencephalogram (EEG) distortion. In this paper, we propose a method for EOG Blinking Artefacts (BAs) detection and removal from EEG. Normalized Correlation Coefficient (NCC), based on a predetermined BA template library was used for detecting the BA. Ensemble Empirical Mode Decomposition (EEMD) was applied to the contaminated region and a statistical algorithm determined which Intrinsic Mode Functions (IMFs) correspond to the BA. The proposed method was applied in simulated EEG signals, which were contaminated with artificially created EOG BAs, increasing the Signal-to-Error Ratio (SER) of the EEG Contaminated Region (CR) by 35dB on average.

关键词： TEMPLATE MATCHING Empirical mode decomposition Artifacts Blinking handicrafts

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