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第35届中国控制会议

作者： Can Wu Ting Zhang Yongqiang Liao Can Wang Guizhong Wu Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences School of Electro-mechanical Engineering Guangdong University of Technology Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences

ISBN: (纸本)9781509009107

This paper presents a practical control strategy used on lower limb exoskeleton to help paraplegic patients to stand up and sit *** can make the process more comfortable and stable no matter the crutches are pressed heavy or *** is particularly efficient to the robots without drivable ankle joints such SIAT *** space was configured to ensure that the real time-generated trajectory won't break the balance of human-robot *** speed of each joint adjusts to the pressure under the crutches so as to relieve the impact from *** result of experiments shows that the self-adaptive control strategy can not only ensure the stability and fitness,but also form an incentive- "more effort paid,more time saved".

关键词： Exoskeleton Stable space Self-adaptive control Standing up process

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A Low-Cost Vision-Based System for Displacement Analysis in Earthquake Research

A Low-Cost Vision-Based System for Displacement Analysis in ...

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RSI/ISM International Conference on robotics and Mechatronics

作者： Bijan Binaee Mahyar Khayatkhoei Hadi Moradi Amirhossein Nazemi Abdollah Hosseini Control and Intelligent Processing Center Advanced Robotics and Intelligent Systems Lab School of ECE University of Tehran Intelligent Systems Research Institute SKKU South Korea School of Civil Engineeringg College of Engineering University of Tehran

ISBN: (纸本)9781467372350

Measuring linear and angular displacement with high accuracy requires expensive equipment and may interfere with the measurements due to sensors weight and size. In this paper, we propose a low cost vision based approach for measuring linear & angular displacement that can make the earthquake research more *** keep detecting process as fast as possible and meet real-time demands, a typical marker with a peculiar color inside chooses and all instructions performed by Intel CVLib filters. So according to the tests, if the minimum requirement are met, the proposed method can detect marker up to 25 frames per second. Finally, a prototype software implemented to analysis functionality and accuracy of proposed algorithm. The results shown that this vision-based method can achieve accuracy of 0.1mm, with an off-the-shelf three pixel per millimeter, and it can be perfectly used instead of traditional instruments such as LVDT.

关键词： Rotoray-displacement tracking displacement tracking LVDT instrumentation shaking table seismology image processing

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Determining mood via emotions observed in face by induction

Determining mood via emotions observed in face by induction

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

作者： Mojgan Hashemian Hadi Moradi Maryam S Mirian Mehdi Tehrani-doost Advanced Robotics and Intelligent Systems Lab University of Tehran Iran School of Electrical and Computer Engineering University of Tehran Iran Department of Psychiatry Tehran University of Medical Science Iran

Determining the mood of a person is an important step in the Human-Robot interaction. In this paper, we propose a human-inspired approach in which the changes in emotions, done using emotion induction, can be used to determine the mood of a person. The emotion induction, which can be done through robot actions or through showing video clips, stimulates changes in the emotions of the person, reducing the observation time needed to estimate mood. Consequently, the changes in the emotions, which are biased by his/her mood can be used by a robot to determine the mood of a person. To do so, we induced happy emotions by showing a comical clip and measured the intensity of each happy and sad emotions, and also the intensity of the neutral state. Then we extracted a feature set, including both time and frequency domain features, which is used to determine the mood of the person. The approach has been implemented and compared to no-emotion-induction approach and shows better results. Based on the classification results, the approach is able to distinguish between good vs. bad moods with the accuracy of 91.5% with 0.1 mean absolute error. But the neutral state was not distinguishable well.

关键词： Mood Robots Accuracy Feature extraction Face Educational institutions Human-robot interaction

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Determining mood using emotional features

Determining mood using emotional features

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International Symposium on Telecommunications, IST

作者： Mojgan Hashemian Amin Nikoukaran Hadi Moradi Maryam S Mirian Mehdi Tehrani-doost Advanced Robotics and Intelligent Systems Lab University of Tehran Iran School of Electrical and Computer Engineering University of Tehran Iran Department of Psychiatry Tehran University of Medical Science Iran

The ability to determine mood is one of fundamental challenges in affective computing. In this paper, we present a novel approach for mood detection via emotional variations. In this approach, the mood is considered as a low magnitude and more stable, i.e. low frequency, emotion that can be detected using emotion detection approaches. A Bayes classification is applied on a feature vector composed of statistical aspects of the intensity of the emotions. The approach has been implemented in which two emotions, i.e. happiness and sadness, and also neutral state, have been targeted to determine the good, bad, and neutral, mood of subjects respectively. A Bayes classification is applied on a feature vector containing statistical aspects of the intensity of the emotions. The obtained Correct Classification Rate (CCR) is 91.1, with 0.09 mean error and variance of 4.9 discriminating good mood vs. neutral.

关键词： Mood Educational institutions Face Videos Computers Mice Accuracy

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Using general sound descriptors for early autism detection

Using general sound descriptors for early autism detection

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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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A HIERARCHICAL REINFORCEMENT LEARNING-BASED APPROACH TO MULTI-ROBOT COOPERATION FOR TARGET SEARCHING IN UNKNOWN ENVIRONMENTS

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CONTROL AND intelligent systems 2013年第4期41卷 1-1页

作者： Cai, Yifan Yang, Simon X. Xu, Xin Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph ON N1G 2W1 Canada College of Mechatronics and Automation National University of Defense Technology Changsha Hunan Province 410073 China

Effective cooperation of multi-robots in unknown environments is essential in many robotic applications, such as environment exploration and target searching. In this paper, a MAXQ and Option combined hierarchical reinforcement learning approach, together with a multi-agent cooperation strategy, are proposed for the real-time cooperation of multi-robots in completely unknown environments. Unlike other algorithms that need an explicit environment model or selected parameters by trial and error, the proposed cooperation method obtains all the required parameters automatically through learning. By integrating segmental options with the MAXQ algorithm, a multi-agent cooperation strategy is designed. In new tasks, the designed cooperation method can control the multi-robot system to complete the task effectively. The simulation results demonstrate that the proposed scheme is able to effectively and efficiently guide a team of robots to cooperatively accomplish target searching tasks in completely unknown environments.

关键词： Hierarchical reinforcement learning multi-robot cooperation com-pletely unknown environment target searching

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欠驱动三连杆机器人的混杂控制方法

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中国科学：信息科学 2013年第2期43卷 287-302页

作者：赖旭芝张镇吴敏潘昌忠中南大学信息科学与工程学院长沙410083 先进控制与智能自动化湖南省工程实验室长沙410083 Advanced Robotics and Intelligent Systems(ARIS) Laboratory School of EngineeringUniversity of Guelph

针对第二关节为被动关节的欠驱动三连杆机器人,提出一种混杂控制方法.欠驱动三连杆机器人的运动空间分为3个阶段:退化阶段、摇起阶段和平衡阶段.首先,在退化阶段,对第三关节构造Lyapunov函数,并针对此函数设计控制律使其连杆相对于前一... 详细信息

针对第二关节为被动关节的欠驱动三连杆机器人,提出一种混杂控制方法.欠驱动三连杆机器人的运动空间分为3个阶段:退化阶段、摇起阶段和平衡阶段.首先,在退化阶段,对第三关节构造Lyapunov函数,并针对此函数设计控制律使其连杆相对于前一连杆自然伸展,使系统退化为类Pendubot机器人;同时基于能量不断增加的思想设计第一关节控制律,以节省后阶段的能量控制时间.其次,在摇起阶段,保持第三关节控制律形式不变;通过仅控制系统能量和同时控制系统能量、角速度两种方法设计第一关节控制律,使系统进入平衡区.最后,对退化后的系统采用线性控制将其稳定在竖直向上不稳定平衡点上.数值仿真结果表明文中所提方法具有控制时间短,所需力矩小等优点.

关键词：欠驱动机械系统机器人混杂控制 Lyapunov函数退化控制能量控制

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Guest Editorial: intelligent Information Technology in Agriculture

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intelligent Automation & Soft Computing 2013年第3期19卷 227-229页

作者： Dong Ren[a] Chunjiang Zhao[b] & Simon X. Yang[c] [a] College of Computer and Information Technology China Three Gorges University Yichang 443002 P.R. China [b] Beijing Research Center for Information Technology in Agriculture Beijing Academy of Agriculture and Forestry Sciences Beijing 100097 P.R. China [c] Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph Ontario N1G 2W1 Canada

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A multiple feature fusion model for image segmentation based on hierarchical visual pathway

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Advances in Information Sciences and Service Sciences 2012年第8期4卷 274-282页

作者： Hu, Dekun Li, Jianping Yang, Simon X. Gregori, Stefano School of Computer Science and Engineering University of Electronic Science and Technology of China China Advanced Robotics and Intelligent Systems Lab School of Engineering University of Guelph Canada

To segment an object from its background in an image for advanced vision processing, this paper presents a novel bio-inspired general framework for image segmentation in complex nature scenes, which is a hierarchical system that mimics the organization of layered early visual area in primate visual cortex. The proposed methodology consists of two typical stages: the first stage is a parallel modular structure including three segmenting operators based on color feature, form feature and texture feature, each of which solves the segmentation problem independently for the same input. Then, a fusion operation, multiple feature fusion segmentation (MFFS), integrates these three feature segmentations together through the backpropagation neuron network (BPNN) in the last stage, which simulates the operation of area following the lateral geniculate nucleus in primary visual cortex. The proposed approach is applied to several segmentation experiments of many single objects in clustering conditions, the result shows that the approach is capable of competing with state-of-the-art systems.

关键词： Neural networks

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An object recognition model with top-down prediction and context

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International Journal of Advancements in Computing Technology 2012年第12期4卷 283-290页

作者： Hu, Dekun Li, Jianping Yang, Simon X. University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu 611731 China University of Guelph School of Engineering Advanced Robotics and Intelligent Systems Lab Guelph ON Canada

Based on the trickle-up and trickle-down process in primate visual pathway, an ideal model for object recognition is researched. Firstly, the information of the low spatial frequency are extracted and passed to high visual cortex, the bank of the objects in memory is activated by this input, so the prediction of the possible candidate objects is pulled out. Then, the information of high spatial frequency, which keeps the invariability and selectivity of an object, is gained through the trickle-up process. With the top-down prediction, the context and the detailed information from trickle-up pathway, the object is recognized by Bayes inference. The performance of the proposed model is proved by several experiments.

关键词： Object recognition

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