2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)最新文献_第2页

Modelling and control of dual-arm free-floating space robot using virtual decomposition control for capturing target 基于虚拟分解控制的双臂自由漂浮空间机器人捕获目标建模与控制

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324716

Xueqian Wang, Bo Xia, Gang Li, Houde Liu, Bin Liang

引用次数: 1

Design and experimental study of compliant joints of robot based on magneto-rheological fluid 基于磁流变液的机器人柔性关节设计与实验研究

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324711

Shibo Cai, Pengfei Wang, Liubin Tian, Fang Xu, Libin Zhang

引用次数: 0

Projection function and hand pointer for user-interface of daily service robot 日常服务机器人用户界面的投影功能和指针

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324748

Yujin Wakita, Hideyuki Tanaka, Y. Matsumoto

引用次数: 2

Acoustic emission monitoring in high-speed micro end-milling based on SVD-EEMD method 基于SVD-EEMD方法的高速微立铣削声发射监测

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324573

Yun Qi, Jinkai Xu, Zhanjiang Yu, Huadong Yu

引用次数: 1

Maxout neurons based deep bidirectional LSTM for acoustic modeling 基于Maxout神经元的深度双向LSTM声学建模

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324646

Yuan Luo, Yu Liu, Yi Zhang, Boyu Wang, Zhou Ye

引用次数: 2

Summary on calibration method of line-structured light sensor 线结构光传感器标定方法综述

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324571

Xi Zhang, Jian Zhang

引用次数: 6

Mapping human hand fingertips motion to an anthropomorphic robotic hand 将人手的指尖运动映射到拟人化的机器人手

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324511

U. Scarcia, R. Meattini, C. Melchiorri

{"title":"Mapping human hand fingertips motion to an anthropomorphic robotic hand","authors":"U. Scarcia, R. Meattini, C. Melchiorri","doi":"10.1109/ROBIO.2017.8324511","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324511","url":null,"abstract":"The mapping of the human intention to a dexterous anthropomorphic robotic hand is still an open issue among researchers. The complexity behind this problems comes mainly from three factors: the kinematics differences between the users and the robotic hand(s); the differences in size and motion capabilities among different users hands; and the high number of degrees of freedom present in an anthropomorphic hand. In this work, we present a procedure for the determination of a linear transformation capable to interface the user and the robot kinematics and therefore to allow a precise and natural control of the mechanical device. The main assumption that we make is that different human hand kinematics differ-with a good approximation-for a scaling factor only, whereas the proportions between the phalanges lengths and the relative orientation of the fingers are kept almost constant in healthy people [1]. We also assume that, being the considered robotic hand highly anthropomorphic, this condition holds also between the user and the robotic hand. In addition, while for a robotic hand the definition of a reference frame fixed to the palm is a free choice, for the human hand tracked with some external system it is completely software dependent. Therefore additional rotational and translational corrective terms have to be introduced to compensate for the different placement of the palm reference frame with respect to the fingers. We have applied this approach to control the UB-Hand IV using a commercial device called Leap Motion, able to track with a good accuracy the pose of the palm and the positions of the key points of the human hand, i.e. the end points of the hand bones [2].","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129785080","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

OS hand: Octopus-inspired self-adaptive underactuated hand with fluid-driven tentacles and force-changeable artificial muscles 操作系统手:受章鱼启发的自适应欠驱动手，带有液体驱动的触手和力可变的人造肌肉

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324386

Yuangen Wei, Wenzeng Zhang

{"title":"OS hand: Octopus-inspired self-adaptive underactuated hand with fluid-driven tentacles and force-changeable artificial muscles","authors":"Yuangen Wei, Wenzeng Zhang","doi":"10.1109/ROBIO.2017.8324386","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324386","url":null,"abstract":"Inspired from flexible bending of octopus' tentacles and outside-driving kind of traditional hand exoskeletons, this paper proposes a novel self-adaptive underactuated multi-fingered hand (OS Hand), which has four flexible tentacles. Each tentacle is similar to an octopus' tentacle, and consists of an artificial muscle which goes through all joints, eight serial-hinged joints, and force-changeable assembly. The force-changeable assembly is mainly composed of a spring and elastic rubber membrane, which is coordinated for stable grasping by a layer of rubber material in the surface of the tentacle. Each tentacle can execute different grasping modes depending on the shapes and dimensions of the objects grasped and grip objects in a gentle and form-fitting manner. The OS Hand combines good qualities of both powerful grasp of traditional grippers and form-fitting grasp of flexible hands. Kinematic analysis and mathematic model disclose the distribution of contact forces and compare the tentacles in the OS Hand with traditional rigid tentacles. Experimental results show that the OS Hand is valid for precise pinching, self-adaptive powerful encompassing, and grasping forces are freely changeable in a wide range. With the advantages of high self-adaptation, various grasp configurations and large range of grasping forces, the OS Hand has a wide range of applications in the area of service robotics which requires a lot of flexible operations of general grasping, moving, and releasing.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128453390","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

A leveling measurement method and its application in robotic systems 一种水准测量方法及其在机器人系统中的应用

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324687

Cheng Li, H. Gu

引用次数: 0

Hand pose estimation and motion recognition using egocentric RGB-D video 基于自中心RGB-D视频的手部姿态估计和运动识别

2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) Pub Date : 2017-12-01 DOI: 10.1109/ROBIO.2017.8324409

Wataru Yamazaki, Ming Ding, J. Takamatsu, T. Ogasawara

{"title":"Hand pose estimation and motion recognition using egocentric RGB-D video","authors":"Wataru Yamazaki, Ming Ding, J. Takamatsu, T. Ogasawara","doi":"10.1109/ROBIO.2017.8324409","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324409","url":null,"abstract":"Manipulation performed by humans contains a lot of information that helps robots to learn how to handle objects. Since hand poses and motions are related to manipulated objects, extracting this information is one of the important tasks for robotics community. This paper presents a framework to recognize human manipulations including hand motions, hand poses, and shapes of manipulated objects using egocentric RGB-D videos. Our framework is straightforward but powerful through the efficient use of depth information and egocentric vision. We estimate hand poses with an example-based method through the limited appearances of the hand in egocentric vision. First, from a sensed point cloud, our framework distinguishes hands, manipulated objects and an environment using skin color detection and limitation on the range of the moving hand. Next, we estimate a hand pose by aligning the extracted hand point cloud with a pre-recorded database of hand point clouds of different poses. The position and orientation of the head-mounted sensor are estimated to acquire the hand motion in the world coordinate system. Then, the type of hand motion is classified using Dynamic Programming matching between a series of velocity vectors of estimated and a database of wrist trajectories. Finally, we experiment the effectiveness of our framework for hand motion recognition to validate our work.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126804372","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: 3