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World Congress on intelligent Control and Automation (WCICA)

作者： Hao Li S.X. Yang Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph ONT Canada

Thinking and intelligence can never be separated from the world. Modern philosophy rests on a new interpretation of the nature and fulfillment of human reason, and disputes about the nature of human reason are the ultimate battles of philosophy. The symbol based AI approach is not practical for real world problems. The world is artificial intelligence's best model. Intelligence can only be determined by the dynamics of interaction with the world. Being is a temporal event inseparable from the understanding of being embodied in Dasein's forms of life. Based on the modern philosophy's spirit, the behavior-based systems interact with real world directly. The constructed AI system based on philosophy has to express all its goals and desires as physical action to affect its environment, and extract all its knowledge from physical sensors. In this study, a fully autonomous mobile robot is built, after a thorough research to the philosophy's origin of the modern AI. In the mobile robot developed, each module itself generates behavior, and improvement in the competence of the system proceeds by adding new modules to the system. The performance of the robot proves that the whole system is stable.

关键词： intelligent robots Artificial intelligence Humans intelligent systems Sensor systems Mobile robots Cybernetics Machine intelligence Councils Casting

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A remote control system using Java and CORBA architecture

A remote control system using Java and CORBA architecture

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World Congress on intelligent Control and Automation (WCICA)

作者： Hao Li S.X. Yang Fangju Wang Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph Canada Computing & Information Science Department University of Guelph Guelph Canada

Membranes hold promise as a new water treatment method of the future. In this study, a device is designed to test the efficiency of membranes. The device is implemented to be controlled remotely. An Internet based remote control system is implemented on the membrane test device to make the users access to it easier. When using the system, a remote operator only needs a general purpose computer with Internet connection to conduct a test. The engineering objective is to perform robust control over the Internet connection. A control architecture that combines computer and the membrane testing hardware is built. This system has two primary parts, the server part and the client part. A server is used to provide the application to the operator to control the hardware. The client part is executed on the remote operator's computer. The client uses a TCP/IP protocol to connect to the server through the Internet. Communication coordination between the client and the server is developed using Java and Common Object Request Broker Architecture (CORBA).

关键词： Control systems Java Biomembranes Internet Web server System testing Computer architecture Hardware Robust control Application software

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Entire region filling in indoor environments using neural networks

Entire region filling in indoor environments using neural ne...

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World Congress on intelligent Control and Automation (WCICA)

作者： Chaomin Luo S.X. Yang M. Meng Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph Canada Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

Entire region filling is a special type of robot path planning strategy that requires the mobile robot to cover every part of the whole workspace, which has many applications such as cleaning robots, vacuum cleaners, painter robots, land mine detectors, lawn mowers, and window cleaners. In this paper, a novel biologically inspired neural network approach is proposed for entire region filling with obstacle avoidance of a mobile cleaning robot in a nonstationary environment. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation or an additive equation derived from Hodgkin and Huxley's (1952) membrane equation. There are only local lateral connections among neurons. Thus the computational complexity linearly depends on the neural network size. The robot path is autonomously generated from the dynamic activity landscape of the neural network and the previous robot location. The proposed model algorithm is computationally efficient. It can deal with an unstructured environment with irregular obstacles. The effectiveness of the proposed model is demonstrated by simulation results.

关键词： Filling Indoor environments Neural networks Mobile robots Equations Cleaning Landmine detection Neurons Computational modeling Path planning

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Real-time area-covering operations with obstacle avoidance for cleaning robots

Real-time area-covering operations with obstacle avoidance f...

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Chaomin Luo S.X. Yang Xiaobu Yuan Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph ONT Canada School of Computer Science Windsor University Windsor ONT Canada

An area-covering operation is a kind of complete coverage path planning, which requires the robot path to cover every part of the workspace, which is an essential issue in cleaning robots and many other robotic applications such as vacuum, robots, painter robots, land mine detectors, lawn mowers, and windows cleaners. In this paper, a novel biologically inspired neural network approach is proposed for complete coverage path planning with obstacle avoidance of a cleaning robot in a nonstationary environment. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation or an additive equation derived from Hodgkin and Huxley's (1952) membrane equation. There are only local lateral connections among neurons. Thus the computational complexity linearly depends on the neural network size. The proposed model algorithm is computationally efficient, and can also deal with changing environment. Simulation results show that the proposed model is capable of planning collision-free complete coverage robot path.

关键词： Cleaning Robots Path planning Neural networks Equations Landmine detection Neurons Computational modeling Detectors Biomembranes

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A new model of the visual feedback coordinate transformation in humans based on disturbance noise and feedback error that accounts for time delays

A new model of the visual feedback coordinate transformation...

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IEEE International Workshop on intelligent Robots and systems (IROS)

作者： E. Oyama K.F. MacDorman T. Maeda S. Tachi A. Agah Science and Technology (AIST) National Institute for Advanced Industrial Science and Technology Tsukuba Ibaraki Japan Intelligent Robotics Laboratory Graduate School of Systems Engineering Wakayama University Wakayama Japan School of Engineering University of Tokyo Bunkyo Tokyo Japan Department of Electrical Engineering and Computer Science University of Kansas Lawrence KS USA

An essential factor in understanding the motor learning capability of humans, is the coordinate transformation learning of the visual feedback controller. Although a number of learning models for the visual feedback controller have been proposed, none has been able to establish a definitive approach. In our previous work, we have suggested a learning model that uses disturbance noise and the feedback error signal to learn the human visual feedback controller's coordinate transformation. However, the model does not fully consider the time delay in the visual feedback control loop. This paper presents a modified learning model taking into account the time delay and the convergence properties of the model. Numerical simulations are presented to illustrate the effectiveness of the proposed approach.

关键词： Humans Delay effects Adaptive control Error correction Biological system modeling Feedback control Convergence Kinematics intelligent robots Velocity control

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Dense range image smoothing using adaptive regularization

Dense range image smoothing using adaptive regularization

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IEEE International Conference on Image Processing

作者： Yiyong Sun Joon-Ki Paik J.R. Price M.A. Abidi Department of Electrical and Computer Engineering Imaging Robotics and Intelligent Systems Laboratory University of Tennessee Knoxville USA Department of Image Engineering Graduate School of Advanced Imaging Science Chung-Ang University Seoul South Korea

We propose an adaptive regularization algorithm for smoothing dense range images using a novel, first order stabilizing function. The stabilizer we suggest is based upon minimizing the reconstructed surface area and is derived in the native, spherical coordinate system of the range scanner. This allows adjustments to be made along only the direction of measurement, thereby preventing the data overlapping problem that can arise in dense images. Adaptation is achieved by adjusting the regularization parameter according to the results of 2D edge analysis. Results indicate effective noise suppression along with well preserved edges and details in the reconstructed, 3D surfaces.

关键词： Smoothing methods Surface reconstruction Image reconstruction Image edge detection intelligent robots Robot kinematics intelligent systems Laboratories Laser noise Noise measurement

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Model development of MIMO nets: a H-EPN based approach

Model development of MIMO nets: a H-EPN based approach

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IEEE Conference on Decision and Control

作者： S. Ramaswamy K.P. Valavanis S. Barber The Laboratory for Intelligent Processes and Systems The Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA The Robotics and Automation Laboratory The Center for Advanced Computer Studies and the Apparel-CIM Center University of Southwestern Louisiana Lafayette LA USA

The construction and analysis of multiple-input multiple-output (MIMO) subnets is discussed. It is shown that hierarchical time-extended Petri nets (H-EPNs) allow the development of structured MIMO subnets through the use of bottom-up Petri net synthesis techniques. The paper analyzes Petri net extensions that allow a truly hybrid approach to Petri net based systems modeling, analysis and development. The case study emphasizes the advantage of the activator arc extension in studying issues such as static priority scheduling, dynamic failure recognition, and rescheduling in manufacturing systems. The SPNP package, suitably modified to handle the H-EPN extensions, is used to analyze the properties of the derived H-EPN model.

关键词： MIMO Petri nets Failure analysis Job shop scheduling Dynamic scheduling Modeling Timing Manufacturing Packaging Solids

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Increasingly intelligent Micromachines

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Control, robotics, and Autonomous systems 1000年第1期5卷 279-310页

作者： Tian-Yun Huang Hongri Gu Bradley J. Nelson 2Current affiliation: Laboratory for Micromachine Intelligence Department of Advanced Manufacturing and Robotics College of Engineering and State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China email: huangtianyun@*** 1Institute of Robotics and Intelligent Systems ETH Zurich Zurich Switzerland email: huangt@ethz.chhgu@ethz.chbnelson@ethz.ch

intelligent micromachines, with dimensions ranging from a few millimeters down to hundreds of nanometers, are miniature systems capable of performing specific tasks autonomously at small scales. Enhancing the intelligence of micromachines to tackle the uncertainty and variability in complex microenvironments has applications in minimally invasive medicine, bioengineering, water cleaning, analytical chemistry, and more. Over the past decade, significant progress has been made in the construction of intelligent micromachines, evolving from simple micromachines to soft, compound, reconfigurable, encodable, multifunctional, and integrated micromachines, as well as from individual to multiagent, multiscale, hierarchical, self-organizing, and swarm micromachines. The field leverages two important trends in robotics research—the miniaturization and intelligentization of machines—but a compelling combination of these two features has yet to be realized. The core technologies required to make such tiny machines intelligent include information media, transduction, processing, exchange, and energy supply, but embedding all of these functions into a system at the micro- or nanoscale is challenging. This article offers a comprehensive introduction to the state-of-the-art technologies used to create intelligence for micromachines and provides insight into the construction of next-generation intelligent micromachines that can adapt to diverse scenarios for use in emerging fields.

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