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Trajectory Tracking Control of Quadrotor Aerial Vehicle

IFAC Proceedings Volumes 2013年第20期46卷 274-279页

作者： Trong-Toan Tran Thanh-Trung Han Shuzhi Sam Ge The Robotics Institute and School of Automation Engineering University of Electronic Science and Technology of China Chengdu 611731 China The Robotics Institute and Institute of intelligent Systems and Information Technology (ISIT) University of Electronic Science and Technology of China Chengdu 611731 China

We address the trajectory tracking control problem of a Quadrotor Aerial Vehicle (QAV) in the presence of the input constraints. To this purpose we propose a passivity-based control strategy to separate the handling constraints. Then, a nonlinear control law is designed by suitably combining the nested saturation technique, barrier Lyapunov function and passivity-based control. In the results, the designed controller ensures that the tracking error converges to the origin, the constraints are satisfied and the QAV will not overturn. Simulation results are provided to illustrate the effectiveness of our proposed approach.

关键词： Quadrotor Helicopter passive control nested saturation control

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Neural Control of Unknown Non-Affine systems by State and Output Feedback

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IFAC Proceedings Volumes 2013年第20期46卷 224-229页

作者： Wei He Dan Deng Zhong-Liang Tang Robotics institute and School of Automation Engineering University of Electronic Science and Technology of China Chengdu 611731 China Institute of Intelligent Systems and Information Technology and School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China

In this paper, we consider the unknown non-affine nonlinear systems with the input deadzone and external disturbance. To solve the deadzone effects, a Radial Basis Function Neural Network (RBFNN) is introduced to approximate the deadzone effects and improve the robustness of the system. Moreover, we estimate the disturbance in another RBFNN. Based on the Lyapunov stability analysis and the support of high-gain observer, the adaptive neural network control is developed via both full-state feedback and output feedback. Simulation studies are proposed to illustrate the control performance. The semiglobally uniform boundedness is guaranteed in the closed-loop systems under the proposed control.

关键词： Non-affine nonlinear system Input Deadzone Radial Basis Function Neural Network (RBFNN) Lyapunov direct method

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Vision guided path planning system for vehicles using infrared landmark

Vision guided path planning system for vehicles using infrar...

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IEEE International Conference on robotics and Biomimetics

作者： Malik Saad Sultan Xiaopeng Chen Nouman Qadeer Tongtong Zhang Huang Qiang Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China Lab of Intelligent Information and Technology School of Computer Science and Technology Beijing Institute of Technology Beijing China

Infrared-landmark based vision navigation system is proposed to reliably guide drivers from starting point to goal following a feasible shortest path in a known indoor or outdoor environment no matter whether it is day or night. What's more, this system is capable of warning drivers about the dangerous zones “like no right turn, no U-turn, damaged road ahead etc” conditions when no visible light is available for human beings, mostly at night. The system consists of Basler camera, designed Infra-Red landmark, our developed software, IR filter and an industrial computer. Each infrared landmark contains a unique ID. Address information and important notes are attached to each ID. Once a landmark is efficiently detected and its ID is recognized, location information related to the corresponding ID is presented. And then Dijkstra's algorithm is efficiently utilized to find a possible shortest path to destination. After that, path is followed with the aid of vision system. Experimental results demonstrate suitability, effectiveness and feasibility in intelligent transportation system.

关键词： Cameras Vehicles Reliability Algorithm design and analysis Optical filters Machine vision Filtering algorithms

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The first ICB* competition on iris recognition

The first ICB* competition on iris recognition

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IEEE International Joint Conference on Biometrics (IJCB)

作者： Man Zhang Jing Liu Zhenan Sun Tieniu Tan Wu Su Fernando Alonso-Fernandez Valérian Némesin Nadia Othman Koichi Noda Peihua Li Edmundo Hoyle Akanksha Joshi Center for Research on Intelligent Perception and Computing Institute of Automation Chinese Academy of Sciences (CN) Department of Automation University of Science and Technology of China (CN) Zhuhai YiSheng Electronics Technology Co Ltd (CN) Halmstad University (SE) Centrale Marseille Institut Fresnel (UMR 7249) (FR) CNRS Télécom SudParis Nihon System Laboratory. Ltd (JP) School of Information and Communication Engineering Dalian University of Technology (CN) University Federal of Rio de Janeiro (BR) Centre for Development of Advanced Computing (IN)

Iris recognition becomes an important technology in our society. Visual patterns of human iris provide rich texture information for personal identification. However, it is greatly challenging to match intra-class iris images with large variations in unconstrained environments because of noises, illumination variation, heterogeneity and so on. To track current state-of-the-art algorithms in iris recognition, we organized the first ICB* Competition on Iris Recognition in 2013 (or ICIR2013 shortly). In this competition, 8 participants from 6 countries submitted 13 algorithms totally. All the algorithms were trained on a public database (e.g. CASIA-Iris-Thousand [3]) and evaluated on an unpublished database. The testing results in terms of False Non-match Rate (FNMR) when False Match Rate (FMR) is 0.0001 are taken to rank the submitted algorithms.

关键词： Iris recognition Databases Image segmentation Magnetic resonance Testing Image edge detection Noise

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Tangent Barrier Lyapunov Functions for the Control of Output-Constrained Nonlinear systems

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IFAC Proceedings Volumes 2013年第20期46卷 449-455页

作者： Zhong-Liang Tang Keng Peng Tee Wei He Institute of Intelligent Systems and Information Technology (ISIT) and School of Computer and Science Engineering University of Electronic Science and Technology of China Chengdu 611731 China Institute for Infocomm Research A *STAR Singapore 138632 Singapore Robotics Institute (RI) and School of Automation Engineering University of Electronic Science and Technology of China Chengdu 611731 China

In this paper, we present a systematic control design for strict-feedback nonlinear systems with output constraints using tangent Barrier Lyapunov Functions (BLFs-Tan). Both symmetric and asymmetric BLF-Tan based backstepping control design methods are developed. It is proved that with the proposed approach and Lyapunov synthesis, the output constraints are not violated, all signals in the closed-loop systems are bounded, and asymptotical tracking is achieved. Through the simulation, we also perform a comparison study between BLF-Tan and the logarithmic BLF (BLF-Log) to illustrate the difference in control performance, and show that the performance of asymmetric BLF-Tan based controller depends on the position of initial tracking error with respect to the transformed constraint boundary.

关键词： Output Constraints Tangent Barrier Lyapunov Functions Backstepping Design

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A Self-organizing Cooperative Hunting by Swarm Robotic systems Based on Loose-preference Rule

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Acta Automatica Sinica 2013年第1期39卷 57-68页

作者： Tian-Yun HUANG Xue-Bo CHEN Wang-Bao XU Zi-Wei ZHOU Zhi-Yong REN School of Control Science and Engineering Dalian University of Technology Dalian 116024 China School of Electronics and Information Engineering Liaoning University of Science and Technology Anshan 114051 China State Key Laboratory of Robotics System Harbin Institute of Technology Harbin 150080 China

A novel self-organizing approach to cooperative hunting by swarm robotic systems is put forward. Firstly, an individual autonomous motion planning is presented, and the cooperative hunting behaviors are mathematically described. According to decomposition of hunting behaviors, the loose-preference rule is established for the individuals to form the ideal hunting formation during the self-organizing process by the interaction between the target and individuals. Then, we employ the proposed rule to design the autonomous motion controller of the individuals. Finally, the stability of self-organizing system is analyzed by Lyapunov stability criteria. Simulations and experiments demonstrate the feasibility and effectiveness of the proposed approach to cooperative hunting by swarm robotic systems.

关键词： Swarm robotic systems self-organizing cooperative hunting loose preference leader emergence

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Dynamical Balance Optimization and Control of Quadruped Robots Under Perturbing External Force

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IFAC Proceedings Volumes 2013年第20期46卷 199-205页

作者： Zhijun Li Sijia Yu Sibang Liu Key Laboratory of Autonomous Systems and Networked Control Ministry of Education College of Automation Science and Engineering South China University of Technology Guangzhou China The Robotics Institute and School of Mechanical Engineering University of Electronic Science and Technology of China Chengdu China 610054 The Robotics Institute and Institute of Intelligent Systems and Information Technology University of Electronic Science and Technology of China Chengdu China 610054

This paper investigates the optimal feet forces distribution and control of quadruped robots under external disturbance forces. First, we formulate a constrained dynamic model of quadruped robots and derive a reduced order dynamical model of motion/force. Consider an external wrench on quadruped robots, the distribution of required forces and moments on the supporting legs of a quadruped robot is handled as a tip-point force distribution and used to equilibrate the external wrench. Then, a gradient neural network is adopted to minimize the optimized objective function with linear equality and inequality constraints, and hybrid motion/force control based on adaptive neural network is used to compensate for the external perturbation in the environment and approximate feedforward force and impedance of the leg joints on line. The verification of the proposed control is conducted using the extensive simulations.

关键词： quadruped robot forces distribution external wrench motion/force control

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TriggerCas: Enabling wireless consrucive collisions

TriggerCas: Enabling wireless consrucive collisions

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Yin Wang Yuan He Dapeng Cheng Yunhao Liu Xiang-yang Li MOE Key Laboratory for Information System Security School of Software TNLIST Tsinghua University China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong China Key Laboratory of Intelligent Information Processing Universities of Shandong China Department of Computer Science Illinois Institute of Technology USA

Constructive Interference (CI) proposed in the existing work (e.g., A-MAC [1], Glossy [2]) may degrade the packet reception performance in terms of Packet Reception Ratio (PRR) and Received Signal Strength Indication (RSSI). The packet reception performance of a set of nodes transmitting simultaneously might be no better than that of any single node transmitting individually. In this paper, we redefine CI and propose TriggerCast, a practical wireless architecture which ensures concurrent transmissions of an identical packet to interfere constructively rather than to interfere non-destructively. CI potentially allows orders of magnitude reductions in energy consumption and improvements in link quality. Moreover, we for the first time present a theoretical sufficient condition for generating CI with IEEE 802.15.4 radio: concurrent transmissions with an identical packet should be synchronized at chip level. Meanwhile, co-senders participating in concurrent transmissions should be carefully selected, and the starting instants for the concurrent transmissions should be aligned. Based on the sufficient condition, we propose practical techniques to effectively compensate propagation and radio processing delays. TriggerCast has 95 th percentile synchronization errors of at most 250ns. Extensive experiments in practical testbeds reveal that TriggerCast significantly improves PRR (from 5% to 70% with 7 concurrent senders, from 50% to 98.3% with 6 senders) and RSSI (about 6dB with 5 senders).

关键词： Delays Synchronization Signal to noise ratio Receivers Wireless sensor networks IEEE 802.15 Standards

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Vehicle kinematics modeling and design of vehicle trajectory generator system

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Journal of Central South University 2012年第10期19卷 2860-2865页

作者：李昭蔡自兴任孝平陈爱斌薛志超 School of Information Science and Engineering Central South University Institute of Intelligent System and Software Central South University Department of Intelligence Science and Technology Central South University National Institute of Metrology College of Computer Science and Information Technology Central South University of Forestry and Technology Faculty of Health Science University of Copenhagen

A trajectory generator based on vehicle kinematics model was presented and an integrated navigation simulation system was *** that the tight relation between vehicle motion and topography,a new trajectory generator for vehicle was proposed for more actual ***,a vehicle kinematics model was built based on conversion of attitude vector in different coordinate ***,the principle of common trajectory generators was ***,combining the vehicle kinematics model with the principle of dead reckoning,a new vehicle trajectory generator was presented,which can provide process parameters of carrier anytime and achieve simulation of typical actions of running ***,IMU(inertial measurement unit) elements were simulated,including accelerometer and *** setting up the simulation conditions,the integrated navigation simulation system was verified by final performance *** result proves the validity and flexibility of this design.

关键词： vehicle kinematics model integrated navigation system track generator IMU element system simulation

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EEG feature extraction and pattern recognition during right and left hands motor imagery in brain-computer interface

EEG feature extraction and pattern recognition during right ...

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2012 5th International Conference on Biomedical engineering and Informatics, BMEI 2012

作者： Liu, Cheng Wang, Hailing Pu, Hui Zhang, Yi Zou, Ling School of Information Science and Engineering Changzhou University Changzhou Jiangsu 213164 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Heilongjiang 150001 China

ISBN: (纸本)9781467311816

At present, it is an important issue to obtain accurate classification of EEG signal in brain-computer interface. We collected the EEG data which are recorded at a sampling rate of 250Hz by EGI-64 scalp electrodes placed according to the international 10/20 system. Firstly, discrete wavelet transform method is used to decompose the average power of the channel C3/C4 and P3/P4 in left and right hands imagine movement during the some experimental period of time. The reconstructed signal of approximation coefficient A6 on the sixth level is selected to build up a feature signal. Secondly, the performances by Fisher Linear Discriminant Analysis and Support Vector Machine methods are compared. The final classifications results show that correct classification rate by Support Vector Machine is higher and gain an ideal classification results, which can establish a basis of real-time BCI application. © 2012 IEEE.

关键词： Feature extraction

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