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international Conference on Information and automation (ICIA)

作者： Ying Tan Songdong Xue Jianchao Zeng Jengshyang Pan Tienszu Pan Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology No. 66 Waliu Road Shanxi 030024 China Department of Electronic Engineering National Kaohsiung University of Applied Sciences 807 Taiwan

As one of valid modeling and coordinated controlling tools, the particle swarm optimization algorithm can be extended for applying to task of swarm robotic search. To gain an insight into effects of key parameters on distributed swarm search, a series of simulations are conducted. In such control algorithm, main parameters including communication range, detection radius, and swarm size are paid close attentions. Similar to ideal “particles”, swarm robots are modeled at an abstract level with the extended particle swarm optimization method. Also, individual robots are designed to be controlled under three-state finite state machine mechanism having SingleSearch, SwarmSearch, and Declaration states. Then, control strategy and algorithm are developed. The statistical results from simulating data indicate the validity of modeling approach. Further, the effects of three parameters on overhead and efficiency of system running come out in compared analysis both of different size swarms and of specific size swarm.

关键词： Robot kinematics Robot sensing systems Particle swarm optimization Communication system control Orbital robotics Cognitive robotics Motion control Intelligent robots Robot control Mobile robots

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Numerical Investigation of Localized Surface Plasmon Resonance (LSPR) based Sensor for Glucose Level Monitoring

Numerical Investigation of Localized Surface Plasmon Resonan...

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First international symposium on Instrumentation, Control, Artificial intelligence, and robotics (ICA-SYMP)

作者： Kawintida Santavanond Charusluk Viphavakit Wisarn Patchoo Hala El-Khozondar Waleed Mohammed Faculty of Engineering International School of Engineering Chulalongkorn University Bangkok Thailand Faculty of Engineering International School of Engineering Intelligent Control Automation of Process Systems Research Unit Chulalongkorn University Bangkok Thailand The Bangkok University Center of Research in Optoelectronics Communications and Computational Systems School of Engineering Bangkok University Pathumthani Thailand Islamic University of Gaza Gaza Palestine The Bangkok University Center of Research in Optoelectronics Communications and Computational Systems School of Engineering Bangkok University Pathumthani Thailand

ISBN: (数字)9781728187600

ISBN: (纸本)9781728187617

This study aims to apply Localized Surface Plasmon Resonance (LSPR), Maxwell Garnett's formula, and Fabry-Perot theory together to design and develop a LSPR enhanced gold colloidal nanoparticles (AuNPs) sensor to be used in biomedical applications such as detection of glucose level in urine for early stage screening of diabetic patients. In this work, the LSPR based sensor has been designed and studied numerically to detect the glucose level from the change in the effective index resulting in a red shift of the absorption peak. The sensors were designed to have various sizes of the gold nanoparticles in a range between 20 nm and 100 nm by having different molar ratio with Trisodium Citrate (TSC) which acts as stabilizer in the synthesis. The maximum possible sensitivity of the sensor can be achieved with 70 nm diameter of gold nanoparticles at 0.2 volume fraction of AuNP to glucose solution.

关键词： Nanoparticles Gold Sensitivity Robot sensing systems Glucose Optical sensors Surface plasmons

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Evaluation of air quality variability in Timișoara, Romania

Evaluation of air quality variability in Timișoara, Romania

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international symposium on Applied computational intelligence and Informatics ( SACI)

作者： Iasmina Gruicin Marian-Emanuel Ionașcu Mircea Popa Faculty of Automation and Computers University Politehnica of Timișoara Timișoara Romania

ISBN: (数字)9781728173771

ISBN: (纸本)9781728173788

This study presents the evaluation and analysis of air pollution levels in Timisoara, Romania, regarding the main air pollutants. We examined diurnal, monthly and seasonal variations, using datasets of measurements from the four existing fixed air quality monitoring stations in Timisoara. The results show that the station TM-1, located in the south of the city, has overall much higher values that the other stations. All pollutants except for ozone show peaks in the diurnal variation in the morning and late in the afternoon, which can be correlated to the traffic rush hours, and fall and winter dominance in the seasonal variation. Ozone variation follows the chemistry of its formation, showing proportional increases with the increase of sunlight and ultraviolet radiation.

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Emotional Behavior Arbitration for automation and Robotic Systems

Emotional Behavior Arbitration for Automation and Robotic Sy...

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ieee international Conference on Industrial Informatics (INDIN)

作者： C. Roesener B. Lorenz K. Vock G. Fodor Faculty of Science and Technology Keio University Yokohama Japan Institute of Computer Technology University of Technology Vienna Vienna Austria Neurologist and psychoanalyst Vienna Austria

Robot-aided care for handicapped and elderly people is expected to be a key factor in future building automation. Teams of specialized service robots shall assist autonomously in tasks of everyday life. To fulfill the demands of this application field, robotic design has to face new challenges in behavioral design. In this paper a new approach for a general architecture of behavior for mobile robots and automation systems is presented. Based on the psychoanalytic model of the human mind, emotional evaluation mechanisms shall facilitate a fast estimation of complex and unpredictable situations based on environmental data acquired by the sensors of the robot. Emotional intelligence is used to narrow the focus of attention leading to a reduction of the computational load, and to improve the cooperative behavior among the robots. In order to show the advantages of the emotional arbitration architecture, the model has been tested in simulations based on the characteristics of an existing mobile robot.

关键词： robotics and automation Mobile robots Intelligent sensors Robot sensing systems Intelligent robots Senior citizens Buildings Service robots Psychology Humans

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Learning to control: a heterogeneous approach

Learning to control: a heterogeneous approach

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ieee international symposium on Intelligent Control (ISIC)

作者： B. Shirazi S. Yih Department of Computer Science and Engineering Southern Methodist University Dallas TX USA

A heterogeneous approach to the design of an intelligent control system is presented. The purpose of such a system is to recreate the human intelligence within a controller. Application areas include autonomous control vehicles, robotics, and power plant controllers. First, the authors analyze the characteristics of the knowledge acquisition process and show that it is an evolutionary process. They further analyze the components of this process, which are then used as a guide to develop an intelligent control system. This analysis shows that the process may consist of a heterogeneous paradigm consisting of symbolic, fuzzy, and connectionist computation models. The knowledge structure and the learning/evolving mechanism are presented in detail. Finally, a program which learns to perform parallel parking is used as an example to show the effectiveness of this approach.< >

关键词： Intelligent control Humans Intelligent robots Control systems Robot control Remotely operated vehicles Mobile robots Power generation Knowledge acquisition computational modeling

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Self-reconfigurable modular robot - experiments on reconfiguration and locomotion

Self-reconfigurable modular robot - experiments on reconfigu...

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ieee international Workshop on Intelligent Robots and Systems (IROS)

作者： A. Kamimura S. Murata E. Yoshida H. Kurokawa K. Tomita S. Kokaji Distributed System Design Research Group AIST Tsukuba Japan Department of Computational Intelligence and Systems Science Tokyo Institute of Technology Midori-ku Yokohama Japan

We have proposed a self-reconfigurable robotic module, which has a very simple structure. The system is capable of not only building a static structure, but also generating a dynamic robotic motion. We have also developed a simulator for the motion planning. In this paper, we present details of the mechanical and electrical designs of the developed module and its control system architecture. Experiments using ten modules demonstrate the robotic configuration change, crawling locomotion and three types of quadruped locomotion.

关键词： Robots Distributed control Shape Permanent magnets robotics and automation Control systems Power supplies Crystallization Distributed algorithms Algorithm design and analysis

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Learning to Solve Nonlinear Optimization Problem with Deep Reinforcement Learning

Learning to Solve Nonlinear Optimization Problem with Deep R...

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ieee international Conference on robotics and Biomimetics

作者： Yue Gao Qiyue Yang Huajian Wu Ming Sun MoE Key Lab of Artificial Intelligence and AI Institute Shanghai Jiao Tong University Shanghai P.R. China Department of Automation Shanghai Jiao Tong University Shanghai P.R. China

ISBN: (纸本)9781665481106

Nonlinear least-squares problems (NLS) are pop-ular in engineering and scientific fields. Traditional optimization methods such as Newton's method and Gaussian-Newton method (GN) suffer from the sensibility to initial values and the high computational complexity. In this paper, we propose LS-DDPG, a robust optimization method utilizing deep rein-forcement learning algorithms to solve nonlinear least-squares problems. The experiment results on synthetic data demonstrate that the proposed method outperforms Newton's method in terms of computation cost, convergence speed and initial values sensibility. In addition, LS-DDPG is utilized on model predictive control (MPC) problems for trajectory planning and tracking tasks in self-driving with longer prediction horizon and higher accuracy than baseline methods.

关键词： Trajectory planning Optimization methods Reinforcement learning Robustness Newton method Task analysis Robots

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Developing and improving transportation systems: The structure and operation of ieee intelligent transportation systems society

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ieee Transactions on Intelligent Transportation Systems 2005年第3期6卷 261-264页

作者： Wang, Fei-Yue Herget, Charles Zeng, Daniel IEEE ITSS Chinese Academy of Sciences Institute of Automation Beijing 100080 China University of Arizona Department of Systems and Industrial Engineering Tucson AZ 85721 United States IEEE ITSS Herget Associates Alameda CA 94501 United States IEEE ITSS University of Arizona Department of Management Information Systems Tucson AZ 85721 United States Program for Advanced Research in Complex Systems University of Arizona Tucson Key Laboratory of Complex Systems and Intelligence Science Chinese Academy of Sciences ITS Department of the IEEE Intelligent Systems IEEE ITS Society IEEE SMC Board of Governors Herget Associates Alameda CA IEEE Standards ITS US Department of Transportation Department of Management Information Systems University of Arizona INFORMS AAAI and ACM IEEE ITS Society Technical Activities of the Chinese Association for Science and Technology United States

This editorial introduces the structure and operation of the ieee Intelligent Transportation Systems Society (ITSS). A brief history of the ITSS is presented, along with its mission, organizational structure, and a re... 详细信息

关键词： Transportation

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Gas Path Parameter Identification of Turbofan Engine for Carrier Aircraft via Hybrid Mutated Pigeon-Inspired Optimization

Gas Path Parameter Identification of Turbofan Engine for Car...

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ieee international Conference on robotics and Biomimetics

作者： Zhaoyu Zhang Haibin Duan Yang Yuan School of Automation Science and Electrical Engineering Beihang University Beijing China Peng Cheng Laboratory Shenzhen China

ISBN: (纸本)9781665481106

Carrier aircraft is a commonly concerned issue in scientific research due to its extensive military use. Turbofan engine has equipped nearly every carrier aircraft to provide propulsion and gas flow. Gas path parameter identification is performed to establish a mathematical component model for dynamic in-loop simulation. In this paper, the identification is transformed into a two-stage optimization problem, solving by bionic intelligent computation and adaptive Newton Raphson (NR) Iteration. Adaptive step-size adjustment is applied in NR and dynamic scale coefficient in cost function brings convergence to the steady state equation of component model. To reduce the difficulty of deciding the initial status, typical mutation mechanism is utilized to enhance the exploitation characteristic of Pigeon-Inspired Optimization, which is effective in searching for the suitable initial value of NR method. Finally, comparative simulation is put forward to prove the satisfactory performance of the novel optimization method towards other typical swarm intelligence algorithm.

关键词： Adaptation models Parameter estimation Atmospheric modeling computational modeling Biological system modeling Military aircraft Mathematical models

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Self-learning path-tracking control of autonomous vehicles using kernel-based approximate dynamic programming

Self-learning path-tracking control of autonomous vehicles u...

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international Joint Conference on Neural Networks (IJCNN)

作者： Xin Xu Hongyu Zhang Bin Dai Han-gen He Institute of Automation College of Mechatronics and Automation National University of Defense Technology Changsha China

With the fast development of robotics and intelligent vehicles, there has been much research work on modeling and motion control of autonomous vehicles. However, due to model complexity, and unknown disturbances from dynamic environment, the motion control of autonomous vehicles is still a difficult problem. In this paper, a novel self-learning path-tracking control method is proposed for a car-like robotic vehicle, where kernel-based approximate dynamic programming (ADP) is used to optimize the controller performance with little prior knowledge on vehicle dynamics. The kernel-based ADP method is a recently developed reinforcement learning algorithm called kernel least-squares policy iteration (KLSPI), which uses kernel methods with automatic feature selection in policy evaluation to get better generalization performance and learning efficiency. By using KLSPI, the lateral control performance of the robotic vehicle can be optimized in a self-learning and data-driven style. Compared with previous learning control methods, the proposed method has advantages in learning efficiency and automatic feature selection. Simulation results show that the proposed method can obtain an optimized path-tracking control policy only in a few iterations, which will be very practical for real applications.

关键词： Vehicles Kernel Mobile robots Vehicle dynamics Dictionaries Gain Algorithm design and analysis

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