2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)最新文献_第3页

Twisting door handles and pulling open doors with a mobile manipulator 转动门把手，用移动机械手拉开门

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2015-12-01 DOI: 10.1109/ROBIO.2015.7418848

Jiajun Li, Jianguo Tao, L. Ding, Haibo Gao, Z. Deng, Ke-rui Xia

引用次数: 8

Design and development of bio-mimetic soft robotic hand with shape memory alloy 形状记忆合金仿生软机械手的设计与研制

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2015-12-01 DOI: 10.1109/ROBIO.2015.7419122

Hyung-Il Kim, Min-Woo Han, Wei Wang, Sung-Hyuk Song, H. Rodrigue, Sung-hoon Ahn

引用次数: 8

Multi-class assembly parts recognition using composite feature and random forest for robot programming by demonstration 利用组合特征和随机森林进行多类装配件识别，并对机器人编程进行了论证

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2015-12-01 DOI: 10.1109/ROBIO.2015.7418850

Yabiao Wang, R. Xiong, Junnan Wang, Jiafan Zhang

引用次数: 1

Verification the feasibility of SIGVerse for human-robot interaction simulation through following task 通过以下任务验证SIGVerse用于人机交互仿真的可行性

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2015-12-01 DOI: 10.1109/ROBIO.2015.7418933

Wenyu Li, Peipei Song, J. T. Tan, Chi Zhu, F. Duan

引用次数: 1

A gyroscope-based inverted pendulum with application to posture stabilization of bicycle vehicle 基于陀螺仪的倒立摆在自行车姿态稳定中的应用

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2015-12-01 DOI: 10.1109/ROBIO.2015.7419084

Hongzhe Jin, Decai Yang, Zhangxing Liu, Xizhe Zang, Ge Li, Yanhe Zhu

{"title":"A gyroscope-based inverted pendulum with application to posture stabilization of bicycle vehicle","authors":"Hongzhe Jin, Decai Yang, Zhangxing Liu, Xizhe Zang, Ge Li, Yanhe Zhu","doi":"10.1109/ROBIO.2015.7419084","DOIUrl":"https://doi.org/10.1109/ROBIO.2015.7419084","url":null,"abstract":"This paper presents a new inverted pendulum system, whose core stabilizing device is designed based on gyroscopic precession effect. Traditional inverted pendulum system, such as inertia wheel pendulum, gains the required balance torque through the control over the acceleration and deceleration of inertia wheel. Considering the issues of the inefficiency, inflexibility and large capability required for motor driver of the traditional inverted pendulum system, the feature of the new inverted pendulum system possesses the advantages of simple structure, quick response, and high efficiency in control. The gyroscopic precession effect of high-speed gyroscopic rotor effectively provides a large torque to realize stable equilibrium of the new inverted pendulum system. Non-disturbance and disturbance balance experiments of the physical prototype and application of the stabilizing device to posture stabilization of bicycle vehicle are presented in this paper. The results showed that the stabilizing device responded quickly and realized stable equilibrium of the new inverted pendulum system efficiently. Besides, the consequence of application validated that the stabilizing device owns a strong anti-interference ability and a good applicability.","PeriodicalId":325536,"journal":{"name":"2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124698135","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

Control of single cell migration induced by robotically controlled microsource 机器人控制微源诱导单细胞迁移的控制

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2015-12-01 DOI: 10.1109/ROBIO.2015.7419059

Hao Yang, Xiangpeng Li, Yong Wang, Dong Sun

引用次数: 1

Robust and efficient 3D motion tracking in robotic assisted beating heart surgery 机器人辅助心脏手术鲁棒高效的三维运动跟踪

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2015-12-01 DOI: 10.1109/ROBIO.2015.7419038

A. Sheikhjafari, H. Talebi, M. Zareinejad

{"title":"Robust and efficient 3D motion tracking in robotic assisted beating heart surgery","authors":"A. Sheikhjafari, H. Talebi, M. Zareinejad","doi":"10.1109/ROBIO.2015.7419038","DOIUrl":"https://doi.org/10.1109/ROBIO.2015.7419038","url":null,"abstract":"This paper, presents a region-based motion tracking scheme to avoid problems caused by the complexity of the heart physical motion in assisted robotic minimally invasive beating heart surgery. Since, performance of region based methods strongly depend upon control points, selecting them in a region with sufficient texture is very important. Unlike previous methods, which control points are selected manually or placed on centers of grid, the novelty of our approach, is automatically selecting control points. By using automatic selection of the control points, performance and precision of motion tracking is improved and it leads to a robust tracking. In addition to increase accuracy and facilitate selection of control points, in proposed method, surgical instruments and specular reflection are detected and eliminated from the image. Finally, a modified version of 3D tracking algorithm based on a Thin-Plate Spline (TPS) deformable model is developed to improve the motion tracking. To evaluate the proposed algorithm, recorded stereo image sequence of an in-vivo data collected with DaVinci surgical robotic platform is fed to the algorithm.","PeriodicalId":325536,"journal":{"name":"2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130325616","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

Detecting optic disk based on structured learning 基于结构化学习的视盘检测

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2015-12-01 DOI: 10.1109/ROBIO.2015.7418923

Zhun Fan, Yibiao Rong, Xinye Cai, Wenji Li, Huibiao Lin, Zefeng Yu, Jiewei Lu

引用次数: 2

Vision development of humanoid head robot SHFR-III 仿人头部机器人SHFR-III的视觉发展

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2015-12-01 DOI: 10.1109/ROBIO.2015.7418998

Xianxin Ke, Benrui Qiu, Jizhong Xin, Yawen Yun

引用次数: 1

Markov blanket based sequential data feature selection for human motion recognition 基于马尔可夫毯子的序列数据特征选择用于人体运动识别

2015 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2015-12-01 DOI: 10.1109/ROBIO.2015.7419077

Chao Zhuang, Hongjun Zhou, Mingyu You, Lei Liu

{"title":"Markov blanket based sequential data feature selection for human motion recognition","authors":"Chao Zhuang, Hongjun Zhou, Mingyu You, Lei Liu","doi":"10.1109/ROBIO.2015.7419077","DOIUrl":"https://doi.org/10.1109/ROBIO.2015.7419077","url":null,"abstract":"Human motion recognition is a hot topic in the field of human-machine interface research, where human motion is often represented in time sequential sensor data. This paper investigates human motion recognition based on feature-selected sequential Kinect skeleton data. We extract features from the Cartesian coordinates of human body joints for machine learning and recognition. As there are errors associated with the sensor, in addition to other uncertain factors, human motion sequential sensor data usually includes some irrelative and error features. To improve the recognition rate, an effective method is to reduce the amount of irrelative and error features from original sequential data. Feature selection methods for static situations, such as photo images, are widely used. However, very few investigations in the literature discuss this with regards to sequential data models, such as HMM (Hidden Markov Model), CRF (Conditional Random Field), DBN (Dynamic Bayesian Network), and so on. Here, we propose a novel method which combines a Markov blanket with the wrapper method for sequential data feature selection. The proposed algorithm is assessed using four sets of human motion data and two types of learners (HMM and DBN), and the results show that it yields better recognition accuracy than traditional methods and non-feature selection models.","PeriodicalId":325536,"journal":{"name":"2015 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124240374","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