2008 IEEE International Conference on Robotics and Biomimetics最新文献_第5页

Performance analysis and optimization of a novel large displacement 3-DOF parallel manipulator 一种新型大位移三自由度并联机器人的性能分析与优化

2008 IEEE International Conference on Robotics and Biomimetics Pub Date : 2009-02-22 DOI: 10.1109/ROBIO.2009.4913011

Y. Yun, Yangmin Li

引用次数: 4

Use of forehead bio-signals for controlling an Intelligent Wheelchair 利用前额生物信号控制智能轮椅

2008 IEEE International Conference on Robotics and Biomimetics Pub Date : 2009-02-22 DOI: 10.1109/ROBIO.2009.4912988

Lai Wei, Huosheng Hu, Kui Yuan

引用次数: 69

Shifted gamma distribution and long-range prediction of Round Trip Timedelay for Internet-based teleoperation 基于互联网的远程操作的移位伽玛分布和远程往返时延预测

2008 IEEE International Conference on Robotics and Biomimetics Pub Date : 2009-02-22 DOI: 10.1109/ROBIO.2009.4913181

Dan Chen, Xiuhui Fu, Wei Ding, Hongyi Li, N. Xi, Yuechao Wang

引用次数: 22

Using neuro-fuzzy control to enhance maneuverability of master-slave system in position feedback frameworks 在位置反馈框架下，利用神经模糊控制增强主从系统的可操作性

2008 IEEE International Conference on Robotics and Biomimetics Pub Date : 2009-02-22 DOI: 10.1109/ROBIO.2009.4913236

W. Po-ngaen

引用次数: 1

A differential magnetic localization method for bionic micro-machine guided by external magnetic field 外磁场引导下仿生微机械的微分磁定位方法

2008 IEEE International Conference on Robotics and Biomimetics Pub Date : 2009-02-22 DOI: 10.1109/ROBIO.2009.4913136

Wang Zhe, Song Tao, Wang Jinguang, Wang Zheng, Y. Cenyu

引用次数: 2

A multi-target tracking algorithm using texture for real-time surveillance 一种基于纹理的实时多目标跟踪算法

2008 IEEE International Conference on Robotics and Biomimetics Pub Date : 2009-02-22 DOI: 10.1109/ROBIO.2009.4913335

Zhixu Zhao, Shiqi Yu, Xinyu Wu, Congling Wang, Yangsheng Xu

引用次数: 13

Preparation for turning a Bucket Wheel Reclaimer into a robotic arm 准备将斗轮取料机改造成机械臂

2008 IEEE International Conference on Robotics and Biomimetics Pub Date : 2009-02-22 DOI: 10.1109/ROBIO.2009.4913259

Tien-Fu Lu

{"title":"Preparation for turning a Bucket Wheel Reclaimer into a robotic arm","authors":"Tien-Fu Lu","doi":"10.1109/ROBIO.2009.4913259","DOIUrl":"https://doi.org/10.1109/ROBIO.2009.4913259","url":null,"abstract":"This paper presents the ground work prepared for turning a Bucket Wheel Reclaimer (BWR) into a robotic arm for operation automation. BWR has been widely used in dealing with bulk materials by removing them from the conveyor and stack them as well as to load stacked materials onto the in-feed conveyor, such as in mining industry. Generally speaking, current BWRs are manually operated, remotely operated, or automated to simply follow predefined trajectory patterns. In order to automatically generate trajectory and manoeuvre BWR to specific stockpiles and locations to reclaim materials for the combined product grade required by customers, knowledge of the product quality distribution among stockpiles and within a stockpile is essential. In addition, a converted BWR system like a robotic arm, which can be automated to manoeuvre according to the needs, is required. This paper focuses on the preparation for converting BWR only and presents the derivation of its forward/inverse kinematics, Jacobian and dynamics. A model based controller is developed as well to move around the converted robotic arm. Simulations are conducted using Matlab/Simulink. The results demonstrate satisfactory performance and prove the initial stage of preparation is successfully completed.","PeriodicalId":321332,"journal":{"name":"2008 IEEE International Conference on Robotics and Biomimetics","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121856998","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: 19

A new optimal control model for reproducing two-point reaching movements of human three-joint arm with wrist joint's freezing mechanism 基于腕部关节冻结机制的人体三关节臂两点到达运动的最优控制模型

2008 IEEE International Conference on Robotics and Biomimetics Pub Date : 2009-02-22 DOI: 10.1109/ROBIO.2009.4913034

T. Matsui

{"title":"A new optimal control model for reproducing two-point reaching movements of human three-joint arm with wrist joint's freezing mechanism","authors":"T. Matsui","doi":"10.1109/ROBIO.2009.4913034","DOIUrl":"https://doi.org/10.1109/ROBIO.2009.4913034","url":null,"abstract":"A new optimal control model of human arms has been developed to simulate two-point reaching movement characteristics for human three-joint arms (shoulder, elbow, and wrist joints) and its fundamental performance has been clarified. The new model is formulated by extending the previous two-joint modified minimum torque-change model to a three-joint model with a freezing mechanism in its wrist joint and incorporating three kinds of energy costs into the previous model's evaluation function. The freezing mechanism is modeled as a feedback controller to simulate the muscle dynamics contracting agonists and antagonists together. Consequently, it was clarified that the wrist joint's freezing mechanism and the minimization of the moment power of joints or the energy consumed by viscosity resistance were important to reproduce two-point reaching movement characteristics for human three-joint arms. This suggests that the new model with the freezing mechanism in its wrist joint functions effectively as a model of the human three-joint arm control mechanism and that the energy optimization can involve the trajectory planning of two-point reaching movements.","PeriodicalId":321332,"journal":{"name":"2008 IEEE International Conference on Robotics and Biomimetics","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122038460","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: 6

A statistical approach towards performance analysis of multimodal biometric systems 多模态生物识别系统性能分析的统计方法

2008 IEEE International Conference on Robotics and Biomimetics Pub Date : 2009-02-22 DOI: 10.1109/ROBIO.2009.4913115

Xiaobu Yuan, Wei Gan

引用次数: 7

Sensor fusion of delay and non-delay signal using Kalman Filter with moving covariance 基于移动协方差卡尔曼滤波的延迟与非延迟信号传感器融合

2008 IEEE International Conference on Robotics and Biomimetics Pub Date : 2009-02-22 DOI: 10.1109/ROBIO.2009.4913316

Sirichai Pornsarayouth, M. Wongsaisuwan

{"title":"Sensor fusion of delay and non-delay signal using Kalman Filter with moving covariance","authors":"Sirichai Pornsarayouth, M. Wongsaisuwan","doi":"10.1109/ROBIO.2009.4913316","DOIUrl":"https://doi.org/10.1109/ROBIO.2009.4913316","url":null,"abstract":"A movement of the omni-directional mobile robot is deflected by a slippage of its wheels, measurement such as acceleration, angular velocity and computer vision should be applied to compensate error from slippage of each wheel. Each sensor has advantages and drawbacks. For example, computer vision(CV) can measure the absolute position and the angle of the robot but it requires much time to process images which causes timing delay. On the other hand, inertial sensors such as accelerometers and gyroscope can swiftly response to its movement. Unfortunately, the position and the angle are obtained by integrating the measured signal which causes accumulated error of estimating the position and angle. In this paper, Kalman Filter is applied to implement fusion of the delay and non-delay data. When a delay signal is available, a classical method, which filter delay signal is re-performing Kalman operation at every step from the time of measured delay signal to current time. Therefore, we proposed method that only need to update the stored covariance between two different time instants. With less computational cost comparing to the classical method and the uniformity of the computation in every iteration, the efficiency of Kalman filter remains the same. Also, this method can be applied to soft-nonlinear case by utilizing Extended Kalman filter.","PeriodicalId":321332,"journal":{"name":"2008 IEEE International Conference on Robotics and Biomimetics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130333377","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: 14