2005 International Symposium on Computational Intelligence in Robotics and Automation最新文献_第4页

Using Horocol to program a society of agents or teams of robots 使用Horocol编程一个由代理人或机器人团队组成的社会

2005 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2005-06-27 DOI: 10.1109/CIRA.2005.1554324

D. Duhaut, Y. L. Guyadec, M. Dubois

引用次数: 3

Self-tuning sliding mode control with smooth control input 具有平滑控制输入的自调谐滑模控制

2005 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2005-06-27 DOI: 10.1109/CIRA.2005.1554345

Y. J. Huang, S. Chang

引用次数: 3

Comparison between micro-objects manipulations in dry and liquid mediums 干燥和液体介质中微物体操作的比较

2005 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2005-06-27 DOI: 10.1109/CIRA.2005.1554360

M. Gauthier, B. L. Walle, C. Clévy

引用次数: 31

Adaptive organization of generalized behavioral concepts for autonomous robots: schema-based modular reinforcement learning 自主机器人广义行为概念的自适应组织:基于模式的模块化强化学习

2005 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2005-06-27 DOI: 10.1109/CIRA.2005.1554342

T. Taniguchi, T. Sawaragi

引用次数: 6

Design of a semiautonomous biomimetic underwater vehicle for environmental monitoring 半自主仿生环境监测水下航行器设计

2005 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2005-06-27 DOI: 10.1109/CIRA.2005.1554247

M. Listak, G. Martin, D. Pugal, A. Aabloo, M. Kruusmaa

引用次数: 28

Linear synchronous motor servo drive based on adaptive wavelet neural network 基于自适应小波神经网络的直线同步电机伺服驱动

2005 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2005-06-27 DOI: 10.1109/CIRA.2005.1554354

F. Lin, Po-Hung Shen

{"title":"Linear synchronous motor servo drive based on adaptive wavelet neural network","authors":"F. Lin, Po-Hung Shen","doi":"10.1109/CIRA.2005.1554354","DOIUrl":"https://doi.org/10.1109/CIRA.2005.1554354","url":null,"abstract":"An adaptive wavelet neural network (AWNN) control system is proposed to control the position of the mover of a permanent magnet linear synchronous motor (PMLSM) servo drive system to track periodic reference trajectories in this study. In the proposed AWNN control system, a WNN with accurate approximation capability is employed to approximate the unknown dynamics of the PMLSM, and a robust term is proposed to confront the inevitable approximation errors due to finite number of wavelet basis functions and disturbances including the friction force. The adaptive learning algorithm that can learn the parameters of weight, dilation and translation of the WNN on line is derived using Lyapunov stability theorem. Moreover, to relax the requirement for the bound of uncertainty in robust term, which comprises a minimum approximation error, optimal parameter vectors, higher-order terms in Taylor series and friction force, an adaptive bound estimation law is investigated where a simple adaptive algorithm is utilized to estimate the bound of uncertainty. Furthermore, the experimental results due to periodic reference trajectories show that the dynamic behaviors of the proposed control systems are robust with regard to uncertainties.","PeriodicalId":162553,"journal":{"name":"2005 International Symposium on Computational Intelligence in Robotics and Automation","volume":"30 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115862938","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: 0

Polyhedral convex cones for computing feasible grasping regions from vision 多面体凸锥计算视觉可行抓取区域

2005 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2005-06-27 DOI: 10.1109/CIRA.2005.1554343

Madjid Boudaba, A. Casals

引用次数: 3

The "what" problem: the emergence of new goals in a robot “什么”问题:机器人中出现的新目标

2005 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2005-06-27 DOI: 10.1109/CIRA.2005.1554337

R. Manzotti, M. Villamira

引用次数: 0

Cooperative reinforcement learning: exploring communication and cooperation problems 合作强化学习:探讨沟通与合作问题

2005 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2005-06-27 DOI: 10.1109/CIRA.2005.1554317

Constança Oliveira e Sousa, L. Custódio

引用次数: 2

Learning by observation of robotic tasks using on-line PCA-based Eigen behavior 基于在线pca特征行为的机器人任务观察学习

2005 International Symposium on Computational Intelligence in Robotics and Automation Pub Date : 2005-06-27 DOI: 10.1109/CIRA.2005.1554308

Xianhua Jiang, Y. Motai

{"title":"Learning by observation of robotic tasks using on-line PCA-based Eigen behavior","authors":"Xianhua Jiang, Y. Motai","doi":"10.1109/CIRA.2005.1554308","DOIUrl":"https://doi.org/10.1109/CIRA.2005.1554308","url":null,"abstract":"This paper presents a new framework for learning the behavior of an articulated body. The motion capturing method has been developed mainly for analysis of human movement, but very rarely used to teach a robot human behavior in an on-line manner. In the traditional teaching method, robotic motion is captured and converted into the virtual world, and then analyzed by human interaction with a graphical user interface. However such a supervised learning framework is often unrealistic since many real-life applications may involve huge datasets in which exhaustive sample-labeling requires expensive human resources. Thus in our learning phase, we initially apply the supervised learning to just small instances using a traditional principal component analysis (PCA) in the off-line phase, and then we apply the incremental PCA learning technique in the on-line phase. Our on-line PCA method maintains the reconstruction accuracy, and can add numerous new training instances while keeping reasonable dimensions of the eigenspace. In comparison to other incremental on-line learning approaches, which use each static image, our proposed method is new since we consider image sequences as a single unit of sensory data. The extensions of these methodologies include the robotic imitation of human behavior at the semantic level. The experimental results using a humanoid robot, demonstrate the feasibility and merits of this new approach for robotic teaching.","PeriodicalId":162553,"journal":{"name":"2005 International Symposium on Computational Intelligence in Robotics and Automation","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122551382","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: 12