2014 IEEE International Conference on Information and Automation (ICIA)最新文献

A magnetic-assistant multi-ocular tracking system 磁辅助多眼跟踪系统

2014 IEEE International Conference on Information and Automation (ICIA) Pub Date : 2014-10-23 DOI: 10.1109/ICINFA.2014.6932745

Qing He, Ningfeng Wei, Chao Hu, M. Meng, Y. Hu

引用次数: 0

Visual recognition of the initial and end points of lap joint for welding robots 焊接机器人搭接头起始点和末端点的视觉识别

2014 IEEE International Conference on Information and Automation (ICIA) Pub Date : 2014-10-23 DOI: 10.1109/ICINFA.2014.6932709

P. Kiddee, Zaojun Fang, M. Tan

引用次数: 20

Structural design and dynamic analysis of biologically inspired water-jumping robot 仿生跳水机器人结构设计与动力学分析

2014 IEEE International Conference on Information and Automation (ICIA) Pub Date : 2014-10-23 DOI: 10.1109/ICINFA.2014.6932848

Jihong Yan, Tao Wang, Xinbin Zhang, Jie Zhao

{"title":"Structural design and dynamic analysis of biologically inspired water-jumping robot","authors":"Jihong Yan, Tao Wang, Xinbin Zhang, Jie Zhao","doi":"10.1109/ICINFA.2014.6932848","DOIUrl":"https://doi.org/10.1109/ICINFA.2014.6932848","url":null,"abstract":"Water strider is an amazing insect that can effortlessly float, quickly run and jump on a water surface without drowning. It's of great challenge and interest to design and fabricates a micro robot that can walk on a water surface like water strider to carry out aquatic tasks such as water quality monitoring, aquatic exploration, water search and rescue. In this study, we designed a new type of biologically inspired water-jumping robot on the basis of the locomotion mechanism of water strider. The lifting force of the supporting legs, the driven force obtained by the actuating legs and the resistant force exerted on the robot are analyzed by simplified models. A dynamic analysis and simulation by ADAMS are performed on the jumping movement of the robot. By optimizing the robot structure, and adjusting the driven mode and the center of gravity location, the robot finally possesses a good jumping performance on water surface in a typical simulation. This study not only offers a better understanding of the water-jumping capability of water strider, but may prove helpful in the research of water strider robots.","PeriodicalId":427762,"journal":{"name":"2014 IEEE International Conference on Information and Automation (ICIA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128341992","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

The modular robot joint design and experience verification for small openings and enclosed space 小开口封闭空间的模块化机器人关节设计与经验验证

2014 IEEE International Conference on Information and Automation (ICIA) Pub Date : 2014-10-23 DOI: 10.1109/ICINFA.2014.6932779

Pengfei Wang, Q. Cao, K. Gu

引用次数: 2

Design of a microscope auto-focusing device based on multi-stage leaf spring 基于多级钢板弹簧的显微镜自动调焦装置设计

2014 IEEE International Conference on Information and Automation (ICIA) Pub Date : 2014-07-28 DOI: 10.1109/ICINFA.2014.6932616

Yilin Liu, Kailin Wu, Daren Xu, Qingsong Xu

引用次数: 4

Friction identification and control for Chinese large-scale space end-effector 中国大型空间末端执行器的摩擦辨识与控制

2014 IEEE International Conference on Information and Automation (ICIA) Pub Date : 2014-07-28 DOI: 10.1109/ICINFA.2014.6932815

F. Ni, Qian Zhang, Shipeng Xie, Hong Liu, Dangyang Jie

引用次数: 1

A hybrid floor identification algorithm based on Bayesian classification and special AP 基于贝叶斯分类和特殊AP的混合楼层识别算法

2014 IEEE International Conference on Information and Automation (ICIA) Pub Date : 2014-07-28 DOI: 10.1109/ICINFA.2014.6932743

Fang Zhao, Dan Luo, Wu Yuan, Haiyong Luo

引用次数: 0

3D interactive virtual environments for minimally invasive vascular surgery 用于微创血管手术的三维交互式虚拟环境

2014 IEEE International Conference on Information and Automation (ICIA) Pub Date : 2014-07-28 DOI: 10.1109/ICINFA.2014.6932769

Shao-Hua Mi, Z. Hou, Fan Yang, Xiaoliang Xie, Guibin Bian

引用次数: 0

From ROS to unity: Leveraging robot and virtual environment middleware for immersive teleoperation 从ROS到unity:利用机器人和虚拟环境中间件实现沉浸式远程操作

2014 IEEE International Conference on Information and Automation (ICIA) Pub Date : 2014-07-28 DOI: 10.1109/ICINFA.2014.6932785

Robert Codd-Downey, P. M. Forooshani, A. Speers, Hui Wang, Michael Jenkin

引用次数: 47

Improving myoelectric pattern recognition using invariant feature extraction 利用不变特征提取改进肌电模式识别

2014 IEEE International Conference on Information and Automation (ICIA) Pub Date : 2014-07-28 DOI: 10.1109/ICINFA.2014.6932694

Jianwei Liu, X. Sheng, Dingguo Zhang, Xiangyang Zhu

{"title":"Improving myoelectric pattern recognition using invariant feature extraction","authors":"Jianwei Liu, X. Sheng, Dingguo Zhang, Xiangyang Zhu","doi":"10.1109/ICINFA.2014.6932694","DOIUrl":"https://doi.org/10.1109/ICINFA.2014.6932694","url":null,"abstract":"The existing algorithms of myoelectric pattern recognition (MPR) are far from enough to satisfy the criteria which an ideal control system for upper extremity prostheses should fulfill. This study focuses on the criterion of short training, or possibly zero training. Due to the non-stationarity inhered in surface electromyography (sEMG) signals, the system may need to be re-trained day by day in the extended usage of myoelectric protheses. However, as the subjects perform the same motion types in different days, we hypothesize there still exists some invariant characteristics in the sEMG signals. Therefore, give a set of training data from several days, it is possible to find an invariant component in them. To this end, an invariant feature space analysis (IFSA) framework based on kernel feature extraction is proposed in this paper. A desired transformation, which minimizes the dissimilarity between sEMG feature distributions of different days and maximizes the dependence between the training data and their corresponding labels, is found. The results show that the generalization ability of the classifier trained on previous days to the unseen testing days can be improved by using IFSA. More specifically, IFSA significantly outperforms Baseline (original input feature) with average classification rate of 1.11% to 1.69% (p <; 0.0001) in task including 9 motion classes or 13 motion classes. This implies that the promising approach can help for achieving the zero-training of MPR.","PeriodicalId":427762,"journal":{"name":"2014 IEEE International Conference on Information and Automation (ICIA)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116193851","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