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The performance of a piezoelectric micro-pump for 3D additive manufacturing

IOP Conference Series: Materials Science and Engineering 2018年第1期409卷

作者： Kai Li Jun-kao Liu Wei-shan Chen Lu Zhang State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Harbin Dongan Engine Corporation LTD Aero Engine Corporation of China Harbin China

The piezoelectric micro-pump is one kind of electronic device which can achieve supplying fluid on demand, and the total volume of fluid per time is at μL level. For fluid, such as fluid base on Cyanoacrylate, with low dynamic viscosity and can be solidified easily, the micro-pump is effectively to be used for 3D additive manufacturing. In this paper, we show a valve less piezoelectric micro-pump with the advantages of simple structure and stable performance. And we analyze the performance of the piezoelectric micro-pump which can be used for 3D additive manufacturing. A fluid solid coupling method is proposed for simulating the working progress of the piezoelectric micro-pump. The fluid transmission performance of the piezoelectric is mainly analyzed, such as the mass flow, flow rate of the outlet and the internal pressure distribution. The working principle of the piezoelectric micro-pump is discussed as well.

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Correction to: Fabrication of high-strength polyoxymethylene fibers by gel spinning

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Journal of Materials Science 2018年第18期53卷 13316-13316页

作者： Xudong Fang Tom Wyatt Jing Shi Donggang Yao School of Mechanical Engineering Xi’an Jiaotong University Xi’an China School of Materials Science and Engineering Georgia Institute of Technology Atlanta USA State Key Laboratory for Manufacturing Systems Engineering Xi’an China State Key Laboratory of Robotics and System (HIT) Harbin China

In the original article, the name of author Donggang Yao was misspelled. It is correct here.

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Building and analyzing of an active robot-assisted surgical navigation for cervical vertebra bone grinding in spine surgery

Advances in Modelling and Analysis C

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Advances in Modelling and Analysis C 2017年第1期72卷 25-47页

作者： Tian, Heqiang Ma, Longxin Dang, Xiaoqing Zhang, Jinfeng Ma, Junlin Mechanical and Electronic Engineering College Shandong University of Science and Technology Qingdao266590 China Qingdao Municipal Hospital Qingdao266073 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150080 China

Surgical navigation has emerged as a potential solution to improve accuracy and security of intraoperative surgery. This paper introduces surgical navigation technologies into cervical vertebra bone grinding in spine surgery to guide a bone-grinding robot. Firstly, an active robot-assisted surgical navigation system based on optical positioning for cervical vertebra bone grinding is created, and the space registration coordinate system among "image-patient-robot" is also established. Secondly, space registration among "image-patient-robot" is studied. Here, intraoperative registration between image and patient is achieved by ICP improved algorithm based on coordinate system direction fitting, and space transformation between patient and robot is established by using an optical locator based on planimetric method. At last, the navigating and positioning precision of robot-assisted spine surgery is analyzed by performing positioning and tracking experiments and the influencing factors for surgical navigation errors are also analyzed. The experiment results show that the active surgical navigation system can achieve positioning and tracking of bone-grinding robot feasibly and rationally. © 2018 AMSE Press. All rights reserved.

关键词： Robots

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Type Synthesis of fully-Decoupled 2T2R Parallel Mechanisms Based on Driven - Chain Principle

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Journal of Harbin Institute of Technology(New Series) 2016年第5期23卷 45-52页

作者： Yi Cao School of Mechanical Engineering Jiangnan University Wuxi Jiangsu 214122 China State Key Laboratory of Robotics and System Harbin 150080 China State Key Laboratory of Mechanical System and Vibration Shanghai 200240 China Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology Wuxi Jiangsu 214122 China

Based on the screw theory and the driven-chain principle,a methodology of structural synthesis for fully-decoupled two-translational(2T) and two-rotational(2R) parallel mechanism is proposed by analyzing the characteristics of the input-output relations for fully-decoupled parallel ***,according to the desired kinematic characteristics of fully-decoupled parallel mechanisms,a method is proposed by virtue of screw theory to synthesize the desired forms for both the direct and the inverse Jacobian ***,according to the feature of the direct and the inverse Jacobian matrices,the effective screws,the actuated screws and the mobile un-actuated screws of each leg are established based on the reciprocal screw theory and all possible topology structures fulfilling the requirements are ***,the desired fully-decoupled parallel mechanisms can be synthesized by using the structural synthesis rule and structural synthesis of fullydecoupled 2T2R parallel mechanisms can be obtained exploiting the abovementioned *** particular,the direct Jacobian matrix of each synthesized fully-decoupled 2T2R parallel mechanism is a non-zero diagonal matrix throughout the entire *** are mounted on each leg and each one of them actuates one degree-of-freedom(Do F) of the fully-decoupled parallel mechanism through a one-to-one velocity relation.

关键词： type synthesis fully-decoupled parallel mechanisms driven-chanin principle screw theory

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A unified leader-follower scheme for mobile robots with uncalibrated on-board camera

A unified leader-follower scheme for mobile robots with unca...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Dejun Guo Hesheng Wang Weidong Chen Ming Liu Zeyang Xia Kam K. Leang DARC (Design Automation Robotics & Control) Lab University of Utah Robotics Center Salt Lake City Utah USA State Key Laboratory of Robotics and System (HIT) Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University Shanghai China Department of Electronics and Computer Engineering Hong Kong University of Science and Technology Hong Kong China Institute of Biomedical and Health Engineering Chinese Academy of Sciences Shenzhen China

This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitable for both omnidirectional and perspective cameras, is proposed. The proposed approach avoids the need for accurate calibration of the extrinsic parameters of the omnidirectional camera as well as the intrinsic and extrinsic parameters of perspective camera. Additionally, the coefficients of the plane where the feature point moves relative to the camera frame can be uncertain. These uncertain constant parameters are estimated using an adaptive estimator. Uniform Semi-global Practical Asymptotic Stability (USPAS) of the system is shown using the Lyapunov approach. Experimental results are presented to demonstrate the effectiveness of the proposed control scheme.

关键词： Cameras Robot vision systems Kinematics Mobile robots Calibration Automation

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On the development of intrinsically-actuated, multisensory dexterous robotic hands

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ROBOMECH Journal 2016年第1期3卷 1-9页

作者： Liu, Hong Yang, Dapeng Fan, Shaowei Cai, Hegao State Key Laboratory of Robotics and System Harbin Institute of Technology HIT Science Park No.2 Yikuang Street Nangang District P.O. Box 3039 Harbin150080 China

Restoring human hand function by mechatronic means is very challenging in robotics research. In this paper, we first make a brief review on the development of dexterous robotic/prosthetic hands, and then detail our design philosophy of several robot hands. We make a concentration on a type of intrinsically-actuated robot hands, wherein the driving, transmission, and control elements are totally embedded in the hand. According to different application scenarios, we develop robot hands in two parallel lines, dexterous robotic hand and anthropomorphic prosthetic hand. In both, the hand’s actuation, sensing, and control subsystems are highly integrated and modularized. This feature endows our robot hands with compact appearances, simple integration, and large flexibilities. At last, we give some perspectives on the future development of dexterous hands from the aspects of structure, functionality, and control strategies. © 2016, Liu et al.

关键词： Robotic arms

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Robot Teaching by Teleoperation Based on Visual Interaction and Neural Network Learning

Robot Teaching by Teleoperation Based on Visual Interaction ...

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2017 9th International Conference on Modelling, Identification and Control (ICMIC 2017)

作者： Yang Xu Chenguang Yang Junpei Zhong Hongbin Ma Lijun Zhao Min Wang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and EngineeringSouth China University of Technology National Institute of Advanced Industrial Science and Technology School of Automation Beijing Institution of Technology State Key Laboratory of Robotics and System Harbin Institute of Technology

Traditional methods of Robot teaching require human demonstrators to program with a teaching pendant,which is a complex and time-consuming *** this paper,we propose a novel method based on teleoperation which allows a demonstrator to train robot in an intuitive *** specifically,at the beginning the demonstrator controls a robot by visual *** then a learning algorithm based on radial basis function(RBF) network is used to transfer the demonstrator's motions to the *** verify the effectiveness of this developed methods,several simulation experiments have been carried out which based on Microsoft Kinect Sensor and the Virtual Robot Experimentation Platform(V-REP).The experimental results show that this method has achieved satisfactory *** the help of this method,the robot can not only complete the task autonomously after teaching,but also can learn the details of demonstrator's behavior.

关键词： Robot Teaching Teleoperation radial basis function(RBF) network

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An auto-docking assembly test system for target suits

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Jiqiren/Robot 2016年第1期38卷 115-121页

作者： Zou, Yu Rong, Weibin Xing, Jiyao Sun, Lining State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

An assembly test platform capable of micrometer positioning, visual and force sensing detection, is developed for suits docking in ignition target final assembly. The classification and discrimination of target parts and the corresponding image detection are adopted to realize closed-loop position control. The target suits docking process is analyzed, and a assembly force model is established. An assembly force control method is proposed based on the established model. Finally, targets positioning and docking experiments are carried out using the developed auto-assembly system, and the system force control, assembly accuracy and efficiency are verified. © 2016, Chinese Academy of Sciences. All right reserved.

关键词： Force control

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MedShapeNet - A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

arXiv

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arXiv 2023年

作者： Li, Jianning Zhou, Zongwei Yang, Jiancheng Pepe, Antonio Gsaxner, Christina Luijten, Gijs Qu, Chongyu Zhang, Tiezheng Chen, Xiaoxi Li, Wenxuan Wodzinski, Marek Friedrich, Paul Xie, Kangxian Jin, Yuan Ambigapathy, Narmada Nasca, Enrico Solak, Naida Melito, Gian Marco Vu, Viet Duc Memon, Afaque R. Schlachta, Christopher De Ribaupierre, Sandrine Patel, Rajnikant Eagleson, Roy Chen, Xiaojun Mächler, Heinrich Kirschke, Jan Stefan de la Rosa, Ezequiel Christ, Patrick Ferdinand Li, Hongwei Bran Ellis, David G. Aizenberg, Michele R. Gatidis, Sergios Küstner, Thomas Shusharina, Nadya Heller, Nicholas Andrearczyk, Vincent Depeursinge, Adrien Hatt, Mathieu Sekuboyina, Anjany Löffler, Maximilian Liebl, Hans Dorent, Reuben Vercauteren, Tom Shapey, Jonathan Kujawa, Aaron Cornelissen, Stefan Langenhuizen, Patrick Ben-Hamadou, Achraf Rekik, Ahmed Pujades, Sergi Boyer, Edmond Bolelli, Federico Grana, Costantino Lumetti, Luca Salehi, Hamidreza Ma, Jun Zhang, Yao Gharleghi, Ramtin Beier, Susann Sowmya, Arcot Garza-Villarreal, Eduardo A. Balducci, Thania Angeles-Valdez, Diego Souza, Roberto Rittner, Leticia Frayne, Richard Ji, Yuanfeng Ferrari, Vincenzo Chatterjee, Soumick Dubost, Florian Schreiber, Stefanie Mattern, Hendrik Speck, Oliver Haehn, Daniel John, Christoph Nürnberger, Andreas Pedrosa, João Ferreira, Carlos Aresta, Guilherme Cunha, António Campilho, Aurélio Suter, Yannick Garcia, Jose Lalande, Alain Vandenbossche, Vicky Van Oevelen, Aline Duquesne, Kate Mekhzoum, Hamza Vandemeulebroucke, Jef Audenaert, Emmanuel Krebs, Claudia van Leeuwen, Timo Vereecke, Evie Heidemeyer, Hauke Röhrig, Rainer Hölzle, Frank Badeli, Vahid Krieger, Kathrin Gunzer, Matthias Chen, Jianxu van Meegdenburg, Timo Dada, Amin Balzer, Miriam Fragemann, Jana Jonske, Frederic Rempe, Moritz Malorodov, Stanislav Bahnsen, Fin H. Seibold, Constantin Jaus, Alexander Marinov, Zdravko Jaeger, Paul F. Stiefelhagen, Rainer Santos, Ana Sofia Lindo, Mariana Ferreira, André Alves, Victor Kamp, Michael Abourayya, Amr Nensa, Felix Hörst, Fabian Brehmer, Alexander Hein Girardetstraße 2 Essen45131 Germany Graz University of Technology Inffeldgasse 16c Graz8010 Austria Graz Austria The Department of Computer Science Johns Hopkins University Malone Hall 3400 N Charles St BaltimoreMD21218 United States Rte Cantonale Lausanne1015 Switzerland The Department of Measurement and Electronics AGH University of Science and Technology Krakow Poland Sierre Switzerland Department of Biomedical Engineering University of Basel Hegenheimermattweg Allschwil167C CH-4123 Switzerland The Boston College 140 Commonwealth Ave Chestnut HillMA02467 United States University Hospital B7-200 339 Windermere Road LondonN6A 5A5 Canada The Department of Radiology Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai200240 China The Research Center for Connected Healthcare Big Data ZhejiangLab Zhejiang Hangzhou311121 China The Faculty of Statistics Technical University Dortmund August-Schmidt-Straße 1 Dortmund44227 Germany The Institute of Mechanics Graz University of Technology Kopernikusgasse 24/IV Graz8010 Austria The Institute of Biomedical Manufacturing and Life Quality Engineering State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China The Department of Cardiac Surgery Medical University Graz Auenbruggerplatz 29 Graz8036 Austria The Department of Diagnostic and Interventional Radiology University Hospital Giessen Justus-Liebig-University Giessen Klinikstraße 33 Giessen35392 Germany The Department of Mechanical Engineering Mehran University of Engineering and Technology Jamshoro Sindh76062 Pakistan The Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China The Geschäftsführender Oberarzt Abteilung für Interventionelle und Diagnostische Neuroradiologie Universitätsklinikum der Technischen Universität München Ismaningerstr. 22 München81675 Germany icometrix Kolonel Be

Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from numerous shape-related publications in premier vision conferences as well as the growing popularity of ShapeNet (about 51,300 models) and Princeton ModelNet (127,915 models). For the medical domain, we present a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. As of today, MedShapeNet includes 23 datasets with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface (API) and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. Exemplary, we present use cases in the fields of classification of brain tumors, skull reconstructions, multi-class anatomy completion, education, and 3D printing. In future, we will extend the data and improve the interfaces. The project pages are: https://***/ and https://***/Jianningli/*** Codes 68T01 © 2023, CC BY.

关键词： Large dataset

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Exploring discriminative views for 3D object retrieval 22nd

Exploring discriminative views for 3D object retrieval

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22nd International Conference on MultiMedia Modeling, MMM 2016

作者： Wang, Dong Wang, Bin Zhao, Sicheng Yao, Hongxun Liu, Hong State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China School of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9783319276700

View-based 3D object retrieval techniques have become prevalent in various fields, and lots of ingenious studies have promoted the development of retrieval performance from different aspects. In this paper, we focus on the 2D projective views that represent the 3D objects and propose a boosting approach by evaluating the discriminative ability of each object’s views. Different from previous works on selecting representative views of query object, we investigate the discriminative information of each view in dataset. By employing the proposed reverse distance metric, we utilize the discriminative information for many to many view set matching. The proposed algorithm is then employed with various features to boost the multi-model graph learning method. We compare our approach with several state of the art methods on ETH-80 dataset and National Taiwan University 3D model dataset. The results demonstrate the effectiveness of our method and its excellent boosting performance. © Springer International Publishing Switzerland 2016.

关键词： Artificial intelligence

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