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

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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A robotic holder of transcranial doppler probe for CBFV auto-searching

A robotic holder of transcranial doppler probe for CBFV auto...

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International Conference on Information and Automation (ICIA)

作者： Quanli Qiu Xiaoping Yang Jia Liu Pandeng Zhang Xinyu Wu Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Shenzhen Guangdong China Key Lab of Advanced Manufacturing Technology Harbin Institute of Technology China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong SAR China

ISBN: (纸本)9781479913329

The operational difficulty of Transcranial Doppler (TCD) limits its use in normal clinical settings. We therefore present a robotic arm consists of five degrees of freedom which are achieved by four motors and one extra flexible spring, to assure appropriate pressure on temporal window. With proper control strategies, the robotic arm can move the TCD probe to automatically search temporal window positions. In this paper, we have developed the first full-automatic ambulatory TCD system, evaluated its reliability and efficiency after many experiments. In view of the validation of the instrument in successful experiments, this probe holder is likely to have great impact on future TCD examination.

关键词： Probes DC motors Robots Equations Mathematical model Force Arteries

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Probabilistic model based image retrieval using hypothesis testing

Probabilistic model based image retrieval using hypothesis t...

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International Conference on Information Engineering and Applications, IEA 2011

作者： Li, Bo Liu, Guoping School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Ministry of Education Beijing China Advanced Control and Network Technology Research Unit University of Glamorgan Glamorgan United Kingdom

ISBN: (纸本)9781447123859

The content based image retrieval (CBIR) is aimed to find the most similar images from a collection of images or a database to the query image according to the visual or semantic similarity. Current image retrieval algorithms mainly focus on feature selection and learning distance metric. Other methods are also proposed to promote the performance such as relevance feedback. But as a whole their performance still can not reach the expectation for application. This paper presents a new framework for image retrieval by introducing the hypothesis testing heory. The rest of this paper is organized as follows: Section II introduces the motivation of the proposed approach and the hypothesis testing problem in image retrieval. Section III is the main part of the paper and in this section the concepts of background model, image model, test ratio and feature extraction that compose the framework are introduced and discussed. Section IV shows the relevant experimental results of the algorithm. © 2012 Springer-Verlag London Limited.

关键词： Semantics

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Research on fractional order controller based on best rational approximation approach

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Journal of Convergence Information technology 2012年第4期7卷 50-58页

作者： Zhao, Huimin Nie, Bing Li, Wen Deng, Wu Software Institute Dalian Jiaotong University Dalian 116028 China Key Laboratory of Numerical Simulation in the Sichuan Provincial College Neijiang Normal University Neijiang 641112 China Artificial Intelligence Key Laboratory of Sichuan Province Sichuan University of Science and Engineering Zigong 643000 China State Key Laboratory of Power Transmission Equipment and System Security and New Technology College of Electrical Engineering Chongqing University Chongqing 400044 China Key Laboratory of advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China

Introduce the basic concept of best rational approximation and constructing procedure of the best rational approximation function in Laplace domain. By an illustrative example the design method of FOC based on best rational approximation is discussed. The performance comparison of transfer functions between the FOC obtained by best rational approximation method and conventional PID shows that it is effective to apply the method in design of FOC, which can guarantee maximum absolute error of amplitude frequency characteristic of approximation function in a given error tolerance.

关键词： Rational functions

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Non-destructive inspection of multi-layered composite using ultrasonic signal processing

Non-destructive inspection of multi-layered composite using ...

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Conference on advanced Materials and Nanotechnology, CAMAN 2009

作者： Ng, S.C. Ismail, N. Ali, Aidy Sahari, Barkawi Yusof, J.M. Chu, B.W. Intelligent System and Robotic Laboratory Institute of Advanced Technology Universiti Putra Malaysia 43400 Serdang Selangor Malaysia Department of Mechanical and Manufacturing Engineering Faculty of Engineering Universiti Putra Malaysia 43400 Serdang Selangor Malaysia

Composites exhibit higher strength and stiffness, better design practice and greater corrosion resistance compare to metal material. However, composites are susceptible to impact damage and the typical damage behaviour in the laminated composites is fibre-breakage and delamination. Detection of failure in laminated composites is complicated compared with ordinary non-destructive testing for metal materials as they are sensitive to echoes drown in noise due to the properties of the constituent materials and the multi-layered structure of the composites. In the current study, the detection of failure in multi-layered composite materials is investigated. To obtain a high probability of defect detection in composite materials, signal processing algorithms were used to resolve echoes associated with defects in glass fibre-reinforced plastics (GRP) detected by using ultrasonic testing. Pulse-echo method with single transducer was used to transmit and receive ultrasound. The obtained signals were processed to reduce noise and to extract suitable features. Results were validated on GRP with and without defects in order to demonstrate the feasibility of the method on defect detection in composites.

关键词： Laminated composites

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Wireless Capsule Endoscopy Video Automatic Segmentation

Wireless Capsule Endoscopy Video Automatic Segmentation

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IEEE International Conference on robotics and Biomimetics

作者： Ran Zhou Baopu Li Zhe Sun Chao Hu Max Q.-H Meng Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China and with Guangdong Provincial Key Laboratory of Robotics and Intelligent System. College of Information Ningbo Institute of Technology Zhejiang University. Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong China and with the Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China.

ISBN: (纸本)9781467321259

Wireless capsule endoscopy (WCE) is an advanced technology that allows diagnosis inside human's digestive tract without invasiveness, however, it is a time-consuming task for clinicians to diagnose due to the large number of frames in video. A novel and efficient algorithm is proposed in this paper to help clinicians segment the WCE video automatically according to stomach, small intestine, and large intestine regions. Firstly, since there are many impurities and bubbles in WCE video frames which add the difficulty of segmentation, a pre-procedure is presented to denote the valid regions in the frames based on color and wavelet texture features. Secondly, the boundaries between adjacent organs of WCE video are estimated in two levels which consist of a rough and a fine level. In the rough level, color feature is utilized to draw a dissimilarity curve between frames and the aim is to find the peak of the curve, which represents the approximate boundary we want to locate. In the fine level, Hue-Saturation histogram color feature in HSI color space and uniform LBP texture feature from grayscale images are extracted. And support vector machine (SVM) classifier is utilized to segment the WCE video into different regions. The experiments demonstrate a promising efficiency of the proposed algorithm and the average precision and recall achieve as high as 94.33% and 89.50% respectively.

关键词： Capsule endoscopy video segmentation color and texture feature SVM

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A highly interpretable fuzzy rule base using ordinal structure for obstacle avoidance of mobile robot

A highly interpretable fuzzy rule base using ordinal structu...

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作者： Samsudin, Khairulmizam Ahmad, Faisul Arif Mashohor, Syamsiah Intelligent System and Robotics Laboratory Institute of Advanced Technology Universiti Putra Malaysia 43400 Serdang Selangor Malaysia Department of Computer and Communication Systems Faculty of Engineering Universiti Putra Malaysia 43400 Serdang Selangor Malaysia

Conventional fuzzy logic controller is applicable when there are only two fuzzy inputs with usually one output. Complexity increases when there are more than one inputs and outputs making the system unrealizable. The ordinal structure model of fuzzy reasoning has an advantage of managing high-dimensional problem with multiple input and output variables ensuring the interpretability of the rule set. This is achieved by giving an associated weight to each rule in the defuzzification process. In this work, a methodology to design an ordinal fuzzy logic controller with application for obstacle avoidance of Khepera mobile robot is presented. The implementation will show that ordinal structure fuzzy is easier to design with highly interpretable rules compared to conventional fuzzy controller. In order to achieve high accuracy, a specially tailored Genetic Algorithm (GA) approach for reinforcement learning has been proposed to optimize the ordinal structure fuzzy controller. Simulation results demonstrated improved obstacle avoidance performance in comparison with conventional fuzzy controllers. Comparison of direct and incremental GA for optimization of the controller is also presented. © 2010 Elsevier B.V. All rights reserved.

关键词： Genetic algorithms

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Development of control program for plant growth parameter analysis in lowland tropical greenhouse

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Journal of Applied Sciences 2011年第3期11卷 592-598页

作者： Wan Ishak, W.I. Yin, Tan Ming Hudzari, R.M. Department of Biological and Agriculture Engineering Faculty of Engineering Universiti Putra Malaysia 43400 UPM Serdang Selangor Malaysia Intelligent System and Robotic Laboratory Institute of Advanced Technology Universiti Putra Malaysia 43400 UPM Serdang Selangor Malaysia

The purpose of this project is to develop control system for environment parameter in the lowland tropical greenhouse using Microcontroller. The plant growth analysis covered both inside and outside greenhouse was presented. The controller was used to monitor the temperature, relative humidity and Vapor Pressure Deficit (VPD) in the planting of chili. The study of VPD is to show air moisture conditions for plant production while taking into account different temperature levels. The controller is used to maintain the ideal VPD inside the greenhouse where it has been done for an experimental greenhouse. The higher temperature inside greenhouse, during the day time, further proves the greenhouse effect. The ideal VPD is about to achieve at midnight where the temperature ranged between 19 and 23°C at relative humidity of 54 to 57%. PIC controller was successfully being used and interfacing with computer (read data). The ability of controlling the environment parameter such as temperature, relative humidity and VPD give great potential for the application of the greenhouse in agriculture plantation. © 2011 Asian Network for Scientific Information.

关键词： Controllers

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Compliant task execution and learning for safe mixed-initiative human-robot operations

Compliant task execution and learning for safe mixed-initiat...

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AIAA Infotech at Aerospace Conference and Exhibit 2011

作者： Dong, Shuonan Conrad, Patrick R. Shah, Julie A. Williams, Brian C. Mittman, David S. Ingham, Michel D. Verma, Vandana Massachusetts Institute of Technology Cambridge MA 02139 United States Jet Propulsion Laboratory California Institute of Technology Pasadena CA 91109 United States Department of Aeronautics and Astronautics United States Department of Aeronautics and Astronautics 77 Massachusetts Ave Cambridge MA 02139 United States Planning Software Systems M/S 301-250D United States System Architectures and Behaviors Group M/S 301-490 United States Advanced Robotic Controls M/S 321-151 United States

ISBN: (纸本)9781600869440

We introduce a novel task execution capability that enhances the ability of in-situ crew members to function independently from Earth by enabling safe and effcient interaction with automated systems. This task execution capability provides the ability to (1) map goal-directed commands from humans into safe, compliant, automated actions, (2) quickly and safely respond to human commands and actions during task execution, and (3) specify complex motions through teaching by demonstration. Our results are applicable to future surface robotic systems, and we have demonstrated these capabilities on JPL's All-Terrain Hex-Limbed Extra-Terrestrial Explorer (ATHLETE) robot. © 2011 by the American institute of Aeronautics and Astronautics, Inc.

关键词： Robots

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Mobile robot's electronic compass calibration based on modified Fourier Neural Network

Mobile robot's electronic compass calibration based on modif...

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IEEE Conference on robotics, Automation and Mechatronics

作者： Gong Kun Deng Fang Ma Tao Gong Kun is with School of Automation Beijing Institute of Technology and Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Beijing China Deng Fang is with School of Automation Beijing Institute of Technology and Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Beijing China Ma Tao is with School of Automation Beijing Institute of Technology and Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing China

In order to improve the precision of the azimuth measured by mobile robot's electronic compass, this paper proposes a new calibration method based on Fourier Neural Network trained by Modified Particle Swarm Optimization (MPSO-FNN). This method makes use of Fourier Neural Network (FNN) to establish the error compensation model of electronic compass's azimuth, and introduces Modified Particle Swarm Optimization (MPSO) algorithm to optimize the weights of neural network. Thus the comparatively accurate error model of azimuth is obtained to compensate the output of electronic compass. This method not only has strong nonlinear approximation capability, but also overcomes the neural networks' shortcomings which are too slow convergence speed, oscillation, and easy to fall into local optimum and sensitive to the initial values. Experimental results demonstrate that after calibrated by this method, the range of azimuth error reduces to -0.35°~0.70° from -3.4°~25.2°, and the average value of absolute error is only 0.30°.

关键词： Compass Azimuth Biological neural networks Particle swarm optimization Training Accuracy Automation

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