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检索条件"任意字段=IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2001"

共 555 条记录，以下是151-160 订阅

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Modification of the Wave Variable Technique for Teleoperation Systems Experiencing Communication Loss

Modification of the Wave Variable Technique for Teleoperatio...

引用

ieee international symposium on computational intelligence in robotics and automation (cira)

作者： Mehmet Ismet Can Dede Sabri Tosunoglu Department of Mechanical Engineering Florida International University Miami FL USA

Researchers have studied teleoperation systems essentially for implementation in critical tasks. Although teleoperation systems require stability apriori, time delays over the communications lines become a major source of instability. During the last two decades several researchers have focused on the time delay problem. The wave variable technique is one of the teleoperation controllers developed to ensure stability under time delays. In this paper, a modified algorithm of the wave variable technique is introduced. The purpose of the modification is to ensure that the slave manipulator tracks the position demand of the master even if there is a communication loss or the wave variable technique fails for a limited time period.

关键词： Humans Delay effects Master-slave Testing Stability Control systems Communication system control Robot control Back Medical control systems

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Investigation of Performance of Distributed Complex Systems Using Information-theoretic Means and Genetic Algorithms

Investigation of Performance of Distributed Complex Systems ...

引用

ieee international symposium on computational intelligence in robotics and automation (cira)

作者： D. W. Repperger R. L. Ewing J. B. Lyons R. G. Roberts Air Force Research Laboratory OH USA Department of Electrical and Computer Engineering FAMU and FSU College of Engineering Tallahassee FL USA

An investigation is conducted into performance measures to evaluate network-centric systems via their information or other flow properties. To approach this problem, concepts are borrowed from Graph Theory Information Theory, and current methods to analyze network-centric systems. A number of tools are presented to help better understand how to measure the flow in distributed networks. The efficacy of the proposed method is demonstrated by taking a known distributed paradigm (logistics system) and examining situations that produce maximum and minimum flow conditions. The optimization problem involving flow variables is computationally complex (NP-hard) and thus is determined via genetic algorithms.

关键词： Genetic algorithms Fluid flow measurement Military computing Man machine systems Graph theory Information analysis computational intelligence robotics and automation USA Councils Robustness

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Minimum-Time Algorithm For Intercepting An Object On The Conveyor Belt By Robot

Minimum-Time Algorithm For Intercepting An Object On The Con...

引用

ieee international symposium on computational intelligence in robotics and automation (cira)

作者： Ik Sang Shin Sang-Hyun Nam Rodney G. Roberts Seungbin B. Moon Department of Mechanical Engineering Kyung Hee University Yongin si South Korea School of Electronics and Information Engineering Cheongju University South Korea Department of Electrical and Computer Engineering Florida State University USA Department of Computer Engineering Sejong University Seoul South Korea

This paper provides a minimum time algorithm to intercept an object on the conveyor belt by robotic manipulator. The goal is that the robot is able to intercept objects on a conveyor line moving at a given speed in minimum time. In order to formulate the problem, we introduce the robot and object arrival time functions, and conclude that the optimal point occurs at the intersection of these two functions. The search algorithm for finding the intersection point between the robot and object arrival time functions are also presented to find the optimal point in real-time.

关键词： Belts Service robots Manipulators Robot vision systems robotics and automation Intelligent robots Moon Tracking Robotic assembly Cameras

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Cross Dock Scheduling Using Genetic Algorithms

Cross Dock Scheduling Using Genetic Algorithms

引用

ieee international symposium on computational intelligence in robotics and automation (cira)

作者： Shayla Ley Sherif Elfayoumy IxReveal Inc. Jacksonville FL USA School of Computing University of North Florida Jacksonville FL USA

Cross docking is a distribution system in which the merchandise received at a warehouse or distribution center is not stocked but immediately prepared for onward shipment. In other words, cross docking is the transfer of inward deliveries from the point of reception directly to the point of delivery with limited or no interim storage. One way to reduce cost in a cross dock terminal is to park incoming and outgoing trucks so that the loads can be efficiently moved across the dock. This means that the distance from loading and unloading is the shortest possible distance. The problem with generating an efficient schedule for the door assignments is that for n incoming and m outgoing trucks there are n!*m! possible solutions. This paper describes a solution to the cross dock scheduling problem using genetic algorithms. To judge the efficiency and accuracy of this solution, four programs were developed to test every possible combination of for small problem sizes (four, five, six, and seven incoming trucks). The results of the efficiency and accuracy testing shows that using genetic algorithms to schedule cross dock trucking operations provides an accurate and timely solution.

关键词： Genetic algorithms Optimal scheduling Biological cells Costs Job shop scheduling Loading Testing computational intelligence robotics and automation USA Councils

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Flexible Modeling of a Long Reach Articulated Carrier: Geometric and Elastic Error Calibration

Flexible Modeling of a Long Reach Articulated Carrier: Geome...

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ieee international symposium on computational intelligence in robotics and automation (cira)

作者： J. Chalfoun C. Bidard D. Keller Y. Perrot G. Piolain CEA LIST Service de Robotique Interactive Fontenay-aux-Roses France Areva Nc Beaumont Hague France

The Interactive robotics Unit of CEA LIST has developed a very challenging robotic carrier (called P.A.C.) which is able to perform high range intervention tasks inside blind hot cells. This long reach multi-link carrier has 11 degrees of freedom (DOF) and weighs less than 30 kg. Due to its size and weight, this large robot manipulator holds lots of elastic and geometric deformations. Hence, it presents very low position accuracy. A mechanical model is developed to take into account the flexibilities of the structure. A calibration method of the robot's parameters is used to further reduce the positioning error of the end effector. This method is first tested by simulation. After encouraging simulation results, an experimental field is made for the calibration of the PAC manipulator. Results show that the adopted flexible model, with the new calibrated parameters, is indeed able to correct and reduce for the system errors.

关键词： Solid modeling Calibration Manipulators Orbital robotics Medical robotics Gravity Intelligent robots Polynomials robotics and automation Earth

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Mixed Reinforcement Learning for Partially Observable Markov Decision Process

Mixed Reinforcement Learning for Partially Observable Markov...

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ieee international symposium on computational intelligence in robotics and automation (cira)

作者： Le Tien Dung Takashi Komeda Motoki Takagi Shibaura Institute of Technology Japan

Reinforcement learning has been widely used to solve problems with a little feedback from environment. Q learning can solve full observable Markov decision processes quite well. For partially observable Markov decision processes (POMDPs), a recurrent neural network (RNN) can be used to approximate Q values. However, learning time for these problems is typically very long. In this paper, Mixed Reinforcement Learning is presented to find an optimal policy for POMDPs in a shorter learning time. This method uses both a Q value table and a RNN. Q value table stores Q values for full observable states and the RNN approximates Q values for hidden states. An observable degree is calculated for each state while the agent explores the environment. If the observable degree is less than a threshold, the state is considered as a hidden state. Results of experiment in lighting grid world problem show that the proposed method enables an agent to acquire a policy, as good as the policy acquired by using only a RNN, with better learning performance.

关键词： Learning Recurrent neural networks Table lookup computational intelligence robotics and automation USA Councils Neurofeedback History Neural networks State-space methods

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Genetic Algorithms Multiobjective Optimization of a 2 DOF Micro Parallel Robot

Genetic Algorithms Multiobjective Optimization of a 2 DOF Mi...

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ieee international symposium on computational intelligence in robotics and automation (cira)

作者： Sergiu-Dan Stan Vistrian Maties Radu Balan Department of Mechanics and Computer Science Technical University of Cluj Napoca Cluj-Napoca Romania

This paper is aimed at presenting a study on the optimization of the Bipod micro parallel robot, which comprises a two-degree-of-freedom (DOF) micro parallel robot with variable struts. The robot workspace is characterized and the inverse kinematics equation is obtained. In the paper, design optimization is implemented with genetic algorithms (GA) for optimization considering transmission quality index, manipulability, stiffness and workspace. Here, intended to show the advantages of using the GA, we applied it to a multicriteria optimization problem of 2 DOF micro parallel robot. Genetic algorithms (GA) are so far generally the best and most robust kind of evolutionary algorithms. A GA has a number of advantages. It can quickly scan a vast solution set. Bad proposals do not affect the end solution negatively as they are simply discarded. The obtained results have shown that the use of GA in such kind of optimization problem enhances the quality of the optimization outcome, providing a better and more realistic support for the decision maker.

关键词： Genetic algorithms Parallel robots robotics and automation Design optimization Kinematics Manipulators Sampling methods computational intelligence USA Councils Equations

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Performance Evaluation Criteria for Autonomous Cleaning Robots

Performance Evaluation Criteria for Autonomous Cleaning Robo...

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ieee international symposium on computational intelligence in robotics and automation (cira)

作者： Sungsoo Rhim Jae-Chang Ryu Kwang-Ho Park Soon-Geul Lee Faculty of Mechanical Engineering Kyung Hee University Yongin si Gyeonggi South Korea Department of Mechanical Engineering Kyung Hee University South Korea Korean Agency of Technology and Standards Gwacheon Gyeonggi South Korea

This paper is a report on the initial trial for its kind in the development of the performance index of the autonomous mobile cleaning robot. The unique characteristic features of the cleaning robot have been identified as autonomous mobility, dust collection, and operation noise. Along with the identification of the performance indices the standardized performance-evaluation methods including the corresponding performance evaluation platform for each indices have been developed as well. The validity of the proposed performance evaluation methods has been demonstrated by applying the proposed evaluation methods on two commercial cleaning robots available in market. The proposed performance evaluation methods can be applied to general-purpose autonomous service robots which will be introduced in the consumer market in near future.

关键词： Cleaning Measurement standards Intelligent robots Mobile robots Navigation robotics and automation IEC standards Mechanical engineering Performance evaluation Service robots

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Execution Engine for Robotic Surgery Support Functions in an Unmanned Operating Room

Execution Engine for Robotic Surgery Support Functions in an...

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ieee international symposium on computational intelligence in robotics and automation (cira)

作者： Shilpa Gulati Edwin H. Jung Chetan Kapoor Robotics Research Group University of Texas Austin USA

An unmanned robotic operating room consists of a tele-operated surgical robot and various other subsystems that perform surgery support functions such as dispensing tools and supplies. Execution Engine for such an operating room has to coordinate the subsystems to perform surgery support functions. A support function consists of a series of tasks along with other constructs such as conditional statements. A task, in turn, is composed of subsystem level actions connected by complex synchronization constraints. Previous research has focused on developing a language for specifying tasks and modeling the constraints between them. We present an approach where a task is specified as a data-structure rather than a language. This has the advantage of implicitly encoding the synchronization constraints in the data-structure itself, making it easy to write, debug and maintain task programs. We model a task as a directed acyclic graph and propose an algorithm to execute the task graph. The algorithm is general and language independent, thus eliminating the need for a special purpose language to specify tasks. We discuss implementation results on an emulated system.

关键词： Engines Surgery Robot kinematics Medical robotics Surges robotics and automation Intelligent robots USA Councils Hardware Collaborative software

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Local Online Support Vector Regression for Learning Control

Local Online Support Vector Regression for Learning Control

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ieee international symposium on computational intelligence in robotics and automation (cira)

作者： Younggeun Choi Shin-Young Cheong Nicolas Schweighofer Department of Computer Science Los Angeles CA USA Department of Electrical Engineering University of Southern California Los Angeles CA USA Biokinesiology Department and the Department of Computer Science University of Southern California Los Angeles CA USA

Support vector regression (SVR) is a class of machine learning technique that has been successfully applied to low-level learning control in robotics. Because of the large amount of computation required by SVR, however, most studies have used a batch mode. Although a recently developed online form of SVR shows faster learning performance than batch SVR, the amount of computation required by online SVR prevent its use in real-time robot learning control, which requires short sampling time. Here, we present a novel method, Local online SVR for Learning control, or LoSVR, that extends online SVR with a windowing method. We demonstrate the performance of LoSVR in learning the inverse dynamics of both a simulated two-joint robot and a real one-link robot arm. Our results show that, in both cases, LoSVR can learn the inverse dynamics on-line faster and with a better accuracy than batch SVR.

关键词： Machine learning Robot control Support vector machines Support vector machine classification robotics and automation Sampling methods Neural networks computational intelligence USA Councils Degradation

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