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International Conference on Unmanned Aircraft systems

作者： Seyyed M. Mehdi Dehghan Hadi Moradi Advanced Robotics and Intelligent Systems laboratory Control and Intelligent Processing Center School of Electrical and Computer Engineering University of Tehran

ISBN: (纸本)9781479923779

In this paper, a new approach for Simultaneous Localization of UAV and RF Sources (SLUS) is proposed. In the UAV-based localization of RF sources, such as a cell phone in a search and rescue mission, the UAV navigation errors are a significant source of localization error. Although the use of GPS can reduce UAV localization error significantly resulting in more accurate RF source localization, however, if the GPS is not available temporarily or permanently, the accuracy of UAV-based localization decreases rapidly. The proposed approach solves these two connected problems, i.e. UAV localization and RF source localization, simultaneously to decrease the error of UAV position estimation and the error of RF sources localization. The prediction of UAV pose is done in parallel to RF source position prediction first. Then the predicted states are augmented and the augmented predicted state information is corrected in SLUS using the range and bearing observations. The simulation results show that this method can reduce RF source's position estimation error and prevent the divergence of UAV navigation in latitude and longitude channels. In the other words, the RF features available in the environment can be used to improve the UAV navigation.

关键词： RF source localization UA V navigation SLAM Kalman filter RSSI AOA

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A multi-step Gaussian filtering approach to reduce the effect of non-Gaussian distribution in aerial localization of an RF source in NLOS condition

A multi-step Gaussian filtering approach to reduce the effec...

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2013 1st RSI/ISM International Conference on robotics and Mechatronics, ICRoM 2013

作者： Dehghan, Seyyed M. Mehdi Moradi, Hadi Advanced Robotics and Intelligent Systems Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781467358118

The hybrid localization using Angle of Arrival (AOA) and Received Strength Signal Indicator (RSSI) of an RF source, such as a cell phone in a search and rescue mission, with unknown power and None Line Of Sight (NLOS) condition have been proven to be advantageous compared to using each method separately. The hybrid approach has been proposed to benefit from both RSSI and AOA measurements. In this paper, the initial hybrid method, which was implemented using particle filters due to the multi-modal/non-Gaussian nature of localization in NLOS condition, has been replaced by a multi-step Gaussian filtering approach which provides nearly similar accuracy with better performance. The proposed method has been implemented using extended Kalman filter and Unscented Kalman filter. The simulation results show that the multi-step Gaussian filtering is comparable to particle filter in all cases with better performance. For further evaluation, the effects of uncertainty in the propagation parameters have been studied to show the robustness of each filter to these uncertainties. © 2013 IEEE.

关键词： Extended Kalman filters

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Path planning for localization of an RF source by multiple UAVs on the Crammer-Rao lower bound

Path planning for localization of an RF source by multiple U...

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2013 1st RSI/ISM International Conference on robotics and Mechatronics, ICRoM 2013

作者： Dehghan, Seyyed M. Mehdi Tavakkoli, Mohammad Saberi Moradi, Hadi Advanced Robotics and Intelligent Systems Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781467358118

This paper presents a path planning approach of several UAVs for Radio Frequency (RF) source localization in None Line Of Sight (NLOS) propagation condition using the Received Signal Strength Indication (RSSI). The paths are planned such that the lower bound of standard deviation of localization error, which is equivalent to the Cramer-Rao Lower Bound (CRLB) of the estimation, minimized at any time. Due to the complexity of Jacobin calculation to perform global CRLB optimization, the local values of CRLBs in the current waypoint and next probable waypoints are used in the steepest decent approach to determine the best path. Furthermore, the complexity is reduced by discretizing the space for UAVs to make the computation feasible. The effect of NLOS propagation on the RSSI measurements is simulated by a log-normal distribution and the last estimation of radio source location is used to calculate the local CRLBs. The proposed approach has been simulated and compared with the basic bio-inspired approach of going toward the sensed direction of the source. The result shows better performance than the basic approach. © 2013 IEEE.

关键词： Antennas

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Path planning for localization of an RF source by multiple UAVs on the Crammer-Rao Lower Bound

Path planning for localization of an RF source by multiple U...

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

作者： Seyyed M. Mehdi Dehghan Mohammad Saberi Tavakkoli Hadi Moradi Advanced Robotics and Intelligent Systems laboratory Control and Intelligent Processing Center School of Electrical and Computer Engineering University of Tehran Tehran Iran

关键词： Jacobian matrices Noise

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A multi-step Gaussian filtering approach to reduce the effect of non-Gaussian distribution in aerial localization of an RF source in NLOS condition

A multi-step Gaussian filtering approach to reduce the effec...

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

关键词： Shadow mapping Atmospheric measurements Particle measurements Scattering Measurement uncertainty Particle filters Equations

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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 Special Issue of intelligent Automation and Soft Computing GUEST EDITORIAL 3S AND PRECISION FARMING FOR AGRICULTURE

A Special Issue of Intelligent Automation and Soft Computing...

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World Automation Congress 2012

作者： DAOLIANG LI SIMON X.YANG EU-China Centre for Information and Communication Technologies China Agricultural University Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph

The global must pay more attention on agriculture to support the huge population on the earth and to promote sustainable *** the development of computing and information technologies such as 3S(GIS,RS and GPS;Geographic Information System,Remote Sensing,and Global Positioning System),computer,mathematics,communication,and their application in

关键词： GPS Automation A Special Issue of intelligent Automation and Soft Computing GUEST EDITORIAL 3S AND PRECISION FARMING FOR AGRICULTURE

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