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2007 International Symposium on Computational Intelligence in Robotics and Automation最新文献

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Intelligent Control of A Multi-agent System based on Multi-objective Behavior Coordination 基于多目标行为协调的多智能体系统智能控制
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382918
N. Kubota, N. Aizawa
{"title":"Intelligent Control of A Multi-agent System based on Multi-objective Behavior Coordination","authors":"N. Kubota, N. Aizawa","doi":"10.1109/CIRA.2007.382918","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382918","url":null,"abstract":"Recently multi-agent systems have been discussed to realize a large size of distributed autonomous systems. This paper proposes an intelligent control of multiple partner robots as one of multi-agent systems. First of all, we discuss the current state of researches on the multi-agent systems. Next, we propose a multi-objective behavior coordination to realize formation behaviors based on the integration of the intelligent control from the local viewpoint of individual intelligence and the spring model from the global viewpoint of collective intelligence. Finally, we discuss the effectiveness of the proposed method through several computer simulation results.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130823300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
A Hybrid and Flexible Genetic Algorithm for the Job-Shop Scheduling Problem Job-Shop调度问题的混合灵活遗传算法
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382867
A. Ferrolho, M. Crisostomo
{"title":"A Hybrid and Flexible Genetic Algorithm for the Job-Shop Scheduling Problem","authors":"A. Ferrolho, M. Crisostomo","doi":"10.1109/CIRA.2007.382867","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382867","url":null,"abstract":"A hybrid and flexible genetic algorithm (HybFlexGA) is presented for the job-shop scheduling problem (JSSP). The JSSP is one of the most difficult production scheduling problems in industry because it requires very large combinational search space and the precedence constraint between machines. The computational results on the well-known benchmark instances show the proposed HybFlexGA is very effective and competitive with other methods presented in the literature.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126688552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
η-Filter: An Evidence Theoretic Approach to Unmanned Ground Vehicle Localization η滤波:一种无人地面车辆定位的证据理论方法
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382888
Veera Jawahar Vibeeshanan, K. Subbarao, B. Huff
{"title":"η-Filter: An Evidence Theoretic Approach to Unmanned Ground Vehicle Localization","authors":"Veera Jawahar Vibeeshanan, K. Subbarao, B. Huff","doi":"10.1109/CIRA.2007.382888","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382888","url":null,"abstract":"In this paper, we present a novel evidence theoretic fusion filler, and its application to the Unmanned Ground Vehicle (UGV) localization problem. The various components of the sensor fusion framework such as the adaptive pre-processing unit, the evidence extraction and combination unit, and the extended Kalman filter are described in detail. The crux of this architecture is the evidence extraction and combination unit that employs a two-pronged approach, one to switch between parametric models, and another to adaptively vary the measurement noise covariance matrix. The process of evidence extraction using fuzzy-type or rule-based techniques, and their subsequent combination using the Dempster's rule for combination are detailed. An experiment is conducted to demonstrate the merits of this UGV localization approach. Finally, we conclude with a brief summary of the results.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115271557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Towards a Sensor Classification Scheme for Robotic Manipulators 机器人机械手传感器分类方案研究
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382854
M. Lima, J. Machado, M. Crisostomo
{"title":"Towards a Sensor Classification Scheme for Robotic Manipulators","authors":"M. Lima, J. Machado, M. Crisostomo","doi":"10.1109/CIRA.2007.382854","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382854","url":null,"abstract":"This paper analyzes the signals captured during impacts and vibrations of a mechanical manipulator. To test the impacts, a flexible beam is clamped to the end-effector of a manipulator that is programmed in a way such that the rod moves against a rigid surface. Several signals are captured and theirs Fourier Transforms are calculated and approximated by trendlines based on a power law formula. A sensor classification scheme based on the frequency spectrum behavior is presented.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122919576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Local Online Support Vector Regression for Learning Control 学习控制的局部在线支持向量回归
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382883
Younggeun Choi, Shin-Young Cheong, N. Schweighofer
{"title":"Local Online Support Vector Regression for Learning Control","authors":"Younggeun Choi, Shin-Young Cheong, N. Schweighofer","doi":"10.1109/CIRA.2007.382883","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382883","url":null,"abstract":"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.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131359273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 24
Analysis and application of a robust identification method 一种鲁棒辨识方法的分析与应用
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382852
A. Janot, P. Vandanjon, M. Gautier, F. Khatounian
{"title":"Analysis and application of a robust identification method","authors":"A. Janot, P. Vandanjon, M. Gautier, F. Khatounian","doi":"10.1109/CIRA.2007.382852","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382852","url":null,"abstract":"Parametric identification requires a good know-how and an accurate analysis. The most popular methods consist in using simply the least squares techniques because of their simplicity. However, these techniques are not intrinsically robust. An alternative consists in helping them with an appropriate data treatment while another choice consists in applying a robust identification method. This paper focuses on an analysis of a robust method called \"the simple refined instrumental variable method\". This method will be applied to a single degree of freedom master arm developed by the CEA Interactive Robotic Unit.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"236 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131578233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Investigation of Performance of Distributed Complex Systems Using Information-theoretic Means and Genetic Algorithms 基于信息论和遗传算法的分布式复杂系统性能研究
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382846
D. Repperger, R. Ewing, J. Lyons, R. G. Roberts
{"title":"Investigation of Performance of Distributed Complex Systems Using Information-theoretic Means and Genetic Algorithms","authors":"D. Repperger, R. Ewing, J. Lyons, R. G. Roberts","doi":"10.1109/CIRA.2007.382846","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382846","url":null,"abstract":"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.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121781332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Facial Identity and Expression Recognition by using Active Appearance Model with Efficient Second Order Minimization and Neural Networks 基于高效二阶最小化和神经网络的主动外观模型的人脸身份与表情识别
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382901
Hyun-Chul Choi, Se-Young Oh
{"title":"Facial Identity and Expression Recognition by using Active Appearance Model with Efficient Second Order Minimization and Neural Networks","authors":"Hyun-Chul Choi, Se-Young Oh","doi":"10.1109/CIRA.2007.382901","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382901","url":null,"abstract":"This paper proposes a technique for real-time recognition of facial Identity and expression which uses the active appearance model (AAM) with efficient second order minimization algorithm and neural network, especially the multilayer perceptron. The efficient second order minimization allows AAM to have the ability of correct convergence with a little loss of frame rate. And the correctly extracted facial shape with AAM prevents the recognition of facial identity and expression from undergoing a large error. In addition, high dimensional feature vectors of facial identity and expression, which consist of facial shape and texture, can be dealt by the multilayer perceptron with a very high recognition rate of over 98%.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"478 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116525532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
An Iterative Fuzzy Segmentation Algorithm for Recognizing an Odor Source in Near Shore Ocean Environments 近海环境中气味源识别的迭代模糊分割算法
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382843
Wei Li
{"title":"An Iterative Fuzzy Segmentation Algorithm for Recognizing an Odor Source in Near Shore Ocean Environments","authors":"Wei Li","doi":"10.1109/CIRA.2007.382843","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382843","url":null,"abstract":"A mission of chemical plume tracing (CPT) in near-shore and ocean environments is to navigate an autonomous underwater vehicle (AUV) to find a chemical plume, to trace the plume to its source, and to declare the source location. It is necessary to recognize the declared odor source by using a visual system. Color images, which were taken in near-shore ocean environments when the source was declared, are very vague due to dim illumination conditions and fluid advection effects. This paper presents an iterative fuzzy segmentation (IFS) algorithm for extracting color components of the chemical plume and the odor source for visual confirmation of the correct declared odor source. The proposed approach might be of general interest in image processing and computer vision.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133944214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Robot-Assisted Sensor Network Deployment and Data Collection 机器人辅助传感器网络部署和数据收集
2007 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2007-06-20 DOI: 10.1109/CIRA.2007.382919
Yang Wang, Changhua Wu
{"title":"Robot-Assisted Sensor Network Deployment and Data Collection","authors":"Yang Wang, Changhua Wu","doi":"10.1109/CIRA.2007.382919","DOIUrl":"https://doi.org/10.1109/CIRA.2007.382919","url":null,"abstract":"Wireless sensor networks have been widely used in many applications such as environment monitoring, surveillance systems and unmanned space explorations. However, poor deployment of sensor devices leads (1) bad network connectivity which makes data communication or data collection very hard; or (2) redundancy of coverage which wastes energy of sensors and causes redundant data in the network. Thus, in this paper, we propose using a mobile robot to assist the sensor deployment and data collection for unmanned explorations or monitoring. We assume that the robot can carry and deploy the sensor devices, and also have certain communication capacity to collect the data from the sensor devices. Given a set of interest points in an area, we study the following interesting problems: (1) how to decide minimum number of sensor devices to cover all the interest points; (2) how to schedule the robot to place these sensor devices in certain position so that the path of the robot is minimum; and (3) after the deployment of sensors, how to schedule the robot to visit and communicate with these sensor devices to collect data so that the path of the robot is minimum. We propose a complete set of heuristics for all these problems and verify the performances via simulation.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114149575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 42
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