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IEEE International Conference on robotics and Automation (ICRA)

作者： G.J. Barlow T.C. Henderson A.L. Nelson E. Grant Center for Robotics and Intelligent Machines Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA School of Computing University of Utah Salt Lake UT USA

Smart Sensor Networks (S-nets) are groups of stationary agents (S-elements) which provide distributed sensing, computation, and communication in an environment. In order to integrate information from individual agents and to efficiently transmit this information to other agents, these devices must be able to create local groups (S-clusters). A leadership protocol that creates static clusters has been previously proposed. Here, we further develop this protocol to allow for dynamic cluster updating. This accommodates on-the-fly network re-organization in response to environmental disturbances or the gain or loss of S-elements. We outline an informal argument for the correctness of this revised protocol. We describe our embedded system implementation of the leadership protocol in simulation and using a colony of robots. Finally, we present results demonstrating both implementations.

关键词： Protocols intelligent sensors Mobile robots Distributed computing Robot sensing systems Mobile communication Clustering algorithms robotics and automation intelligent robots Embedded system

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Effects of quantization, saturation, and sampling time in multi output systems

Effects of quantization, saturation, and sampling time in mu...

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IEEE Conference on Decision and Control

作者： R. Sandoval-Rodriguez C.T. Abdallah R.H. Byrne Electrical & Computer Engineering Department Faculty of Electrical Engineering and Computing Albuquerque NM USA Sandia National Laboratories Intelligent Systems and Robotics Center Albuquerque NM USA

ISBN: (纸本)0780386825

We analyze the effects of sampling and quantization in the states of the plant, and the saturation of the control signal, on the behaviors of closed-loop systems. We present graphical and analytical tools to determine the minimum number of bits in the A/D converters, and the maximum sampling time to ensure stability of closed-loop LTI single input multiple output systems.

关键词： Quantization Sampling methods Control systems Communication system control Signal resolution State feedback intelligent robots Signal analysis Communication networks Chaos

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Autonomous controller design for unmanned aerial vehicles using multi-objective genetic programming

Autonomous controller design for unmanned aerial vehicles us...

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Congress on Evolutionary Computation

作者： C.K. Oh G.J. Barlow US Naval Research Laboratory Washington D.C. DC USA Center for Robotics and Intelligent Machines Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA

Autonomous navigation controllers were developed for fixed wing unmanned aerial vehicle (UAV) applications using multiobjective genetic programming (GP). We designed four fitness functions derived from flight simulations and used multiobjective GP to evolve controllers able to locate a radar source, navigate the UAV to the source efficiently using on-board sensor measurements, and circle closely around the emitter. Controllers were evolved for three different kinds of radars: stationary, continuously emitting radars, stationary, intermittently emitting radars, and mobile, continuously emitting radars. We selected realistic flight parameters and sensor inputs to aid in the transference of evolved controllers to physical UAVs.

关键词： Unmanned aerial vehicles Genetic programming Erbium Robot kinematics Robot control Automatic control Radar intelligent robots Mobile robots Navigation

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Evolution of complex autonomous robot behaviors using competitive fitness

Evolution of complex autonomous robot behaviors using compet...

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International Conference on Integration of Knowledge Intensive Multi-Agent Systems (KIMAS)

作者： A.L. Nelson E. Grant G. Barlow M. White Center for Robotics and Intelligent Machines Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA

Evolutionary robotics (ER) employs population-based artificial evolution to develop behavioral robotics controllers. We focus on the formulation and application of a fitness selection function for ER that makes use of intra-population competitive selection. In the case of behavioral tasks, such as game playing, intra-population competition can lead to the evolution of complex behaviors. In order for this competition to be realized, the fitness of competing controllers must be based mainly on the aggregate success or failure to complete an overall task. However, because initial controller populations are often subminimally competent, and individuals are unable to complete the overall competitive task at all, no selective pressure can be generated at the onset of evolution (the bootstrap problem). In order to accommodate these conflicting elements in selection, we formulate a bimodal fitness selection function. This function accommodates subminimally competent initial populations in early evolution, but allows for binary success/failure competitive selection of controllers that have evolved to perform at a basic level. Large arbitrarily connected neural network-based robot controllers were evolved to play the competitive team game Capture the Flag. Results show that neural controllers evolved under a variety of conditions were competitive with a hand-coded knowledge-based controller and could win a modest majority of games in a large tournament.

关键词： Robot kinematics Erbium Robot control robotics and automation Automatic control intelligent robots Mobile robots Control systems Robot sensing systems Artificial neural networks

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Developing evolutionary neural controllers for teams of mobile robots playing a complex game

Developing evolutionary neural controllers for teams of mobi...

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IEEE International Conference on Information Reuse and Integration (IRI)

作者： A.L. Nelson E. Grant G. Lee Center for Robotics and Intelligent Machines Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA Department of Electrical and Computer Engineering San Diego State University San Diego CA USA

This research develops methods of automating the production of behavioral robotics controllers. Population-based artificial evolution was employed to train neural network-based controllers to play a robotic version of the team game Capture the Flag. The robot agents used processed video data for sensing their environment. To accommodate the 35 to 150 sensor inputs required, large neural networks of arbitrary connectivity and structure were evolved. An intra-population competitive genetic algorithm was used and selection at each generation was based on whether the different controllers won or lost games over the course of a tournament. This paper focuses on the evolutionary neural controller architecture. Evolved controllers were tested in a series of competitive games and transferred to real robots for physical verification.

关键词： Mobile robots Automatic control Games Robot sensing systems robotics and automation Artificial neural networks Production Robot control Genetic algorithms Testing

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A colony of robots using vision sensing and evolved neural controllers

A colony of robots using vision sensing and evolved neural c...

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IEEE International Workshop on intelligent Robots and Systems (IROS)

作者： A.L. Nelson E. Grant G.J. Barlow T.C. Henderson Center for Robotics and Intelligent Machines Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA School of Computing University of Utah Salt Lake UT USA

This paper describes the development and testing of a new evolutionary robotics research test bed. The test bed consists of a colony of small computationally powerful mobile robots that use evolved neural network controllers and vision based sensors to generate team game-playing behaviors. The vision based sensors function by converting video images into range and object color data. Large evolvable neural network controllers use these sensor data to control mobile robots. The networks require 150 individual input connections to accommodate the processed video sensor data. Using evolutionary computing methods, the neural network based controllers were evolved to play the competitive team game Capture the Flag with teams of mobile robots. Neural controllers were evolved in simulation and transferred to real robots for physical verification. Sensor signals in the simulated environment are formatted to duplicate the processed real video sensor values rather than the raw video images. Robot controllers receive sensor signals and send actuator commands of the same format, whether they are driving physical robots in a real environment or simulated robots agents in an artificial environment. Evolved neural controllers can be transferred directly to the real mobile robots for testing and evaluation. Experimental results generated with this new evolutionary robotics research test bed are presented.

关键词： Robot sensing systems Robot vision systems Testing Mobile robots Neural networks Image sensors Robot control computer networks Games Computational modeling

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Using Genetic Algorithms to Capture Behavioral Traits Exhibited by Knowledge Based Robot Agents 15

Using Genetic Algorithms to Capture Behavioral Traits Exhibi...

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15th International Conference on computer Applications in Industry and engineering, CAINE 2002

作者： Nelson, A.L. Grant, E. Lee, Gordon Center for Robotics and Intelligent Machines Department of Electrical and Computer Engineering North Carolina State University RaleighNC27695-7911 United States Department of Electrical and Computer Engineering San Diego State University 5500 Campanile Drive San DiegoCA92182 United States

ISBN: (纸本)9781618395351

One of the fundamental issues in the field of Evolutionary robotics (ER) is that of selection and formulation of an appropriate performance training metric. In recent years, proof-of-concept studies have shown that simple behavioral robotics problems, such as homing and foraging, are amenable to ER methods. However, the question of scalability remains unresolved. Several researchers have shown that straightforward ER methods fail to produce viable results on more complex problems if the problem is not partitioned or preprocessed in some fashion before applying ER methods. In many cases, the knowledge required to preprocess the problem is equivalent to that which would be needed to formulate a purely rule knowledge-based controller, hence, in such cases, ER methods provide no real benefit. In this work, we present research results of an investigation into the feasibility of using observed behavior in an environment to train artificial neural network-based robotic controllers to function in that same environment. Robot agents were allowed to navigate through a selection of artificial life simulation environments under the influence of knowledge-based controllers. At each time-step, the simulated robot sensor inputs and actuator outputs were recorded. The resulting input and output data were used to train artificial neural network based controllers for the different environments. The resulting neural network based controllers were then used to control robots in similar environments and were found to exhibit features of the original knowledge-based controllers. Copyright © (2002) by the International Society for computers and Their Applications All rights reserved.

关键词： Knowledge based systems

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Augmenting computer graphics with haptics for the visualization of vessel networks

Augmenting computer graphics with haptics for the visualizat...

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Pacific Conference on computer Graphics and Applications

作者： Dingrong Yi V. Hayward Department of Electrical and Computer Engineering & Center For Intelligent Machines McGill University Montreal QUE Canada

ISBN: (纸本)0769517846

Current visualization methods of volume angiograms are limited in their ability to display vessel connectivity and depth information readily available in the data set. In this paper, we introduce a hybrid graphic-haptic display technique that allows visualizing vessel connectivity as well as provides user assistance in tracing vessel branches. Most importantly, our display provides three-dimensional shape cues in both visual and haptic domains that eliminate the need for a rotational display for 3D perception. Issues related to haptic rendering, implementation, and experimental validation of the developed system are reported. This proposed multimodal visualization approach is independent of the devices used and can be applied to current visualization platforms for angiograms due to the small computational load it requires.

关键词： computer graphics Haptic interfaces Rendering (computer graphics) Application software Angiography Data visualization Shape computer displays Three dimensional displays Magnetic resonance

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Skeletonization of volumetric angiograms for display

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computer Methods in Biomechanics and Biomedical engineering 2002年第5期5卷 329-341页

作者： Yi, Dingrong Hayward, Vincent Department of Electrical and Computer Engineering Center for Intelligent Machines McGill University 3480 University Street Montreal QC H3A 2A7 Canada

The display of three-dimensional angiograms can benefit from the knowledge of quantitative shape features such as tangent and curvature of the centerline of vessels. These can be obtained from a curvelike skeleton representation. If connectivity and topology are preserved, and if geometrical constraints such as smoothness and centeredness are satisfied, it is possible to estimate length, orientation, curvature, and torsion. It is also required that no part of the original object be left unrepresented. An efficient method for the identification of such shape components is developed. First, a suitable representation is obtained using a voxel coding approach to yield connected and labeled unit-thick paths. The desired features are estimated from a smoothed version of the skeleton produced by a moving average filter. The computational cost is linear, of the order of Nobject, the total number of object voxels contained in the binary volumetric data. The method is also shown to be robust to boundary noise. Examples are discussed. © 2002 Taylor & Francis Ltd.

关键词： Volumetric analysis

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Analysis of integrated grasp stiffness matrix with manipulator parameters

Analysis of integrated grasp stiffness matrix with manipulat...

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作者： Ghafoor, Abdul Dai, Jian S. Duffy, Joseph College of Electrical and Mechanical Engineering National University of Sciences and Technology Peshawar Road Rawalpindi - 46000 Pakistan Department of Mechanical Engineering King's College University of London Strand London WC2R 2LS United Kingdom Department of Mechanical Engineering Center for Intelligent Machines and Robotics University of Florida PO Box 116300 Gainesville FL 32611-6300 United States

ISBN: (纸本)0791836215

This paper discusses the integration of grasp with manipulator parameters. The grasp mechanism is considered to be at the end of a serial manipulator. The operation of the grasp and manipulator are independent to each other but the paper describes how their movability can be integrated to achieve the desirable movement of a grasped object. The induction of movement of a grasped object mounted at an end-effector when subjected to an externally applied force system is presented here. The force is considered to be applied at the object and the effect incurs an infinitesimal displacement at the end-effector. The motions of the object and the end-effector have been analysed and associated using the infinitesimal loading. This generates an integrated grasp stiffness matrix associated with manipulator parameters based on fine displacement of an object. The paper presents a novel approach to analyse the grasp stiffness matrix integrated with manipulator parameters. It has shown how infinitesimal and gross movement to the grasped object can be combined which has applications in manufacturing and working environments. Copyright © 2002 by ASME.

关键词： End effectors

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