检索结果-内蒙古大学图书馆

arXiv 2018年

作者： Zhong, Junpei Cangelosi, Angelo Zhang, Xinzheng Ogata, Tetsuya Artificial Intelligence Research Center National Institute of Advanced Industrial Science and Technology Tokyo Japan Centre for Robotics and Neural Systems Plymouth University PlymouthPL4 8AA United Kingdom School of Electrical Engineering Jinan University Zhuhai China Lab for Intelligent Dynamics and Representation Waseda University Tokyo Japan

— The predictive processing (PP) hypothesizes that the predictive inference of our sensorimotor system is encoded implicitly in the regularities between perception and action. We propose a neural architecture in which such regularities of active inference are encoded hierarchically. We further suggest that this encoding emerges during the embodied learning process when the appropriate action is selected to minimize the prediction error in perception. Therefore, this predictive stream in the sensorimotor loop is generated in a top-down manner. Specifically, it is constantly modulated by the motor actions and is updated by the bottom-up prediction error signals. In this way, the top-down prediction originally comes from the prior experience from both perception and action representing the higher levels of this hierarchical cognition. In our proposed embodied model, we extend the PredNet Network, a hierarchical predictive coding network, with the motor action units implemented by a multi-layer perceptron network (MLP) to modulate the network top-down prediction. Two experiments, a minimalistic world experiment, and a mobile robot experiment are conducted to evaluate the proposed model in a qualitative way. In the neural representation, it can be observed that the causal inference of predictive percept from motor actions can be also observed while the agent is interacting with the environment. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Passivity-based stability in explicit force control of robots

Passivity-based stability in explicit force control of robot...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Ribin Balachandran Mikael Jorda Jordi Artigas Jee-Hwan Ryu Oussama Khatib Department for Analysis and Control of Advanced Robotic Systems German Aerospace Center (DLR) Germany Robotics Lab Stanford University Stanford USA BioRobotics Laboratory of Korea University of Technology and Education Cheonan Korea

Direct force control of robots is challenging, particularly since the interaction with the environment can render the robot unstable. This paper presents the results of novel approaches for passivity-based stability for a particular direct force control method, namely explicit force control. A step-by-step procedure to passivate and stabilise the control loop is presented and it explains how Time Domain Passivity Approach, a passivity-based tool widely used in teleoperation and haptics has been extended and applied in explicit force control. The electrical circuit and network-port representations derived in the process allows the analytical evaluation of the system and can be applied in other control architectures as well. The stability methods are presented both qualitatively and quantitatively with simulations and hardware experiments. A discussion about the results obtained and the energy behavior is also provided. Results are promising and suggest that these methods can be used for stable and high-bandwidth force control of robotic manipulators.

关键词： Force Force control Robots Iron Stability criteria Ports (Computers)

来源：评论

学校读者我要写书评

暂无评论

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

arXiv

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

2017 IEEE International Conference on robotics and Automation, ICRA 2017

作者： Guo, Dejun Wang, Hesheng Chen, Weidong Liu, Ming Xia, Zeyang Leang, Kam K. Lab University of Utah Robotics Center Salt Lake CityUT84112 United States Department of Automation Shanghai Jiao Tong University Shanghai200240 China Department of Electronics and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong Institute of Biomedical and Health Engineering Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781509046331

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. © 2017 IEEE.

关键词： Mobile robots

来源：评论

学校读者我要写书评

暂无评论

Multi-stage feature learning based object recognition and 3D pose estimation with kinect 6

Multi-stage feature learning based object recognition and 3D...

引用

6th International Conference on Information Science and technology, ICIST 2016

作者： Zeng, Wei Liang, Guoyuan Guangdong, Can Wang Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Dept. Mechanical and Automation Engineering Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781509012206

Impressive achievements have been achieved over the years in object recognition and 3D pose estimation while detecting objects and estimating their 3D poses reliably is still a very challenging problem, especially for texture-less objects in heavily cluttered scenes. In this paper, we introduce an improved approach based on multi-stage feature learning to identify object as well as their 3D orientation efficiently. Our approach is motivated by visual neuroscience models. Currently similar architectures have been successfully applied to pedestrian detection, traffic recognition, face representation, etc. We compute the feature descriptors by multi-stage convolutional neural networks (CNNs) which could map the object identity and 3D poses to the Euclidean distance space by evaluating the similarity between descriptors. By contrast with classical approaches, our method relies on fast and approximate Nearest Neighbor (NN) matching to solve the large scale problems instead of one classifier per object or multi-class classifiers whose complexity grows rapidly with the number of objects. The experiments of detecting poorly-textured objects in cluttered scenarios have been carried out to verify the effectiveness and efficacy of the proposed approach. © 2016 IEEE.

关键词： Object recognition

来源：评论

学校读者我要写书评

暂无评论

Part-based Grasp Planning for Familiar Objects

Part-based Grasp Planning for Familiar Objects

引用

IEEE-RAS International Conference on Humanoid Robots

作者： Nikolaus Vahrenkamp Leonard Westkamp Natsuki Yamanobe Eren E. Aksoy Tamim Asfour High Performance Humanoid Technologies Lab Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology (KIT) Germany Intelligent Systems Research Institute National Institute of Advanced Industrial Science and Technology (AIST) Japan

ISBN: (纸本)9781509047192

In this work, we present a part-based grasp planning approach that is capable of generating grasps that are applicable to multiple familiar objects. We show how object models can be decomposed according to their shape and local volumetric information. The resulting object parts are labeled with semantic information and used for generating robotic grasping information. We investigate how the transfer of such grasping information to familiar objects can be achieved and how the transferability of grasps can be measured. We show that the grasp transferability measure provides valuable information about how successful planned grasps can be applied to novel object instances of the same object category. We evaluate the approach in simulation, by applying it to multiple object categories and determine how successful the planned grasps can be transferred to novel, but familiar objects. In addition, we present a use case on the humanoid robot ARMAR-III.

关键词： Grasping Planning Shape Semantics Robot sensing systems Training Grasp Manipulator sensing systems Semantics Functional training Portability Planning Shape semiotics

来源：评论

学校读者我要写书评

暂无评论

Self-adaptive Control Strategy for Exoskeleton to Help Paraplegic Patients Stand Up and Sit Down

Self-adaptive Control Strategy for Exoskeleton to Help Parap...

引用

第35届中国控制会议

作者： Can Wu Ting Zhang Yongqiang Liao Can Wang Guizhong Wu Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences School of Electro-mechanical Engineering Guangdong University of Technology Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences

ISBN: (纸本)9781509009107

This paper presents a practical control strategy used on lower limb exoskeleton to help paraplegic patients to stand up and sit *** can make the process more comfortable and stable no matter the crutches are pressed heavy or *** is particularly efficient to the robots without drivable ankle joints such SIAT *** space was configured to ensure that the real time-generated trajectory won't break the balance of human-robot *** speed of each joint adjusts to the pressure under the crutches so as to relieve the impact from *** result of experiments shows that the self-adaptive control strategy can not only ensure the stability and fitness,but also form an incentive- "more effort paid,more time saved".

关键词： Exoskeleton Stable space Self-adaptive control Standing up process

来源：评论

学校读者我要写书评

暂无评论

A Human Motion Prediction Algorithm Based on HSMM for SIAT's Exoskeleton

A Human Motion Prediction Algorithm Based on HSMM for SIAT's...

引用

第35届中国控制会议

作者： Min Wang Xinyu Wu Du-Xin Liu Can Wang Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Department of Mechanical and Automation The Chinese University of Hong Kong

ISBN: (纸本)9781509009107

Getting the exoskeleton pilot's motion intent is very important for exoskeleton *** this paper,a new approach to predict human motion is *** prediction method is based on Hidden Semi-Markov *** orientation of the pilot's segment is collected by the Inertial Measurement *** Adaptive Boosting algorithm is adopted to classify the orientation data into *** sequence of motion labels is inputted into Hidden Semi-Markov Models for motion *** experimental data validate the proposed method.

关键词： Adaptive Boosting Hidden Semi-Markov Model Human Motion Prediction Exoskeleton

来源：评论

学校读者我要写书评

暂无评论

A Hierarchical Emotion Regulated Sensorimotor Model:Case Studies

A Hierarchical Emotion Regulated Sensorimotor Model:Case Stu...

引用

第28届中国控制与决策会议

作者： Junpei Zhong Rony Novianto Mingjun Dai Xinzheng Zhang Angelo Cangelosi Centre for Robotics and Neural Systems Plymouth University Laboratory for Intelligent Dynamics and Representation Waseda University Centre of Quantum Computation and Intelligent Systems University of Technology Shenzhen Key Lab of Advanced Communication and Information Processing and Shenzhen Key Laboratory of Media Security Shenzhen University School of Electrical and Information Engineering Jinan University

ISBN: (纸本)9781467397155

Inspired by the hierarchical cognitive architecture and the perception-action model(PAM)[14],we propose that the internal status acts as a kind of common-coding representation which affects,mediates and even regulates the sensorimotor *** regulation can be depicted in the Bayesian framework,that is why cognitive agents are able to generate behaviours with subtle differences according to their emotion or recognize the emotion by perception.A novel recurrent neural network called recurrent neural network with parametric bias units(RNNPB) runs in three modes,constructing a two-level emotion regulated learning model,was further applied to testify this theory in two different cases.

关键词： Embodied Emotion Modelling Cognitive Architecture Recurrent Neural Networks Non-verbal Emotion Expression Social robotics

来源：评论

学校读者我要写书评

暂无评论

CPG-Based Gait Transition of a Quadruped Robot

CPG-Based Gait Transition of a Quadruped Robot

引用

RSI/ISM International Conference on robotics and Mechatronics

作者： Farhad Asadi Mahdi Khorram S. Ali A. Moosavian Center of Excellence in Robotics and Control Advanced Robotics & Automated Systems (ARAS) Lab Department of Mechanical Engineering K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781467372350

Quadruped animals have high agility and grace skills in the motion over natural environment. An important feature of such animals is their abilities in the selection of appropriate gait in the response to the terrain irregularities and also the smooth transition between them in order to increase the stability or conserve the energy. In this paper, a Cartesian CPG-based controller for the gait generation and the transition between them will be developed. The proposed approach uses nonlinear coupled oscillators for generating rhythmic signals. These patterns can be modulated by a programmed excitation signal and proportionally changing the frequency, amplitude and the coupling parameters among oscillators. According to these variations, the step length, duration of swing and stance phases of all legs, relative phase between the legs and the sequence of leg lifting can be adjusted smoothly especially by the duration of gait transition. Then, trajectories of swing legs along the z- and x-axeis will be computed through the data obtained form the CPG controller. The reference ZMP path will be desgined on the basis of the footprints of legs. Then, the COG trajectories will be calculated with a preview servo controller. Finally, some simulations are conducted to verify the effectiveness of the proposed approach both in the gait generation and smooth gait transition for a quadruped robot.

关键词： central pattern generator Gait transition Walking and Trotting gait quadruped robots Pattern gait generation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：