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International Joint Conference on Neural Networks (IJCNN)

作者： Yiwen Chen Zhaojie Ju Chenguang Yang School of Automation Science and Engineering South China University of Technology Guangzhou China School of Computing University of Portsmouth Portsmouth UK Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Picking up the clustered objects is always a challenging task in robot research field. And reinforcement learning enables robot to adapt to different tasks through plenty of attempts. To reduce the complexity of strategy learning, we propose a framework for robots to pick up the objects in clutter on table based on deep reinforcement learning and rule-based method. To manipulate the objects on table, we mainly divide the robot actions into two categories: one is pushing that uses the reinforcement learning method, while the other one is grasping that is inferred by image morphological processing. The pushing action can separate the stacking objects, create a robust grasp point for the following grasp. The grasp detect algorithm determines if there is a suitable grasp point. Judging on the result of pushing, the grasp detect algorithm will return a reward for pushing learning. Taking images as input, our framework can keep a high grasp rate with low computational complexity, which makes it achieve clutter clearing quickly.

关键词： Reinforcement learning Grasping Robot kinematics Task analysis Clutter Grippers

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A Miniaturised Neuromorphic Tactile Sensor integrated with an Anthropomorphic Robot Hand

A Miniaturised Neuromorphic Tactile Sensor integrated with a...

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2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Benjamin Ward-Cherrier Jörg Conradt Manuel G. Catalano Matteo Bianchi Nathan F. Lepora University of Bristol and Bristol Robotics Laboratory University of Bristol UK School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Istituto Italiano di Tecnologia Genova Italia Universita di Pisa Pisa Italia

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

Restoring tactile sensation is essential to enable in-hand manipulation and the smooth, natural control of upper-limb prosthetic devices. Here we present a platform to contribute to that long-term vision, combining an anthropomorphic robot hand (QB SoftHand) with a neuromorphic optical tactile sensor (neuroTac). Neuromorphic sensors aim to produce efficient, spike-based representations of information for bio-inspired processing. The development of this 5-fingered, sensorized hardware platform is validated with a customized mount allowing manual control of the hand. The platform is demonstrated to succesfully identify 4 objects from the YCB object set, and accurately discriminate between 4 directions of shear during stable grasps. This platform could lead to wide-ranging developments in the areas of haptics, prosthetics and telerobotics.

关键词： Neuromorphics Tactile sensors Hardware Optical sensors Object recognition Telerobotics Prosthetics

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Bacteria Flagella-Mimicking Polymer Multilayer Magnetic Microrobots

SSRN

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SSRN 2024年

作者： Wu, Zhiguang Lu, Liang Bai, Shuang Shi, Jiaqi Zhang, Zhuotao Pan, Yunlu Wang, Wei Wu, Wenfeng Sun, Shoubin Li, Xu Hou, Gang Huang, Tianyun Jia, Yuxin Zuo, Kaiwen Granovsky, Alexander Wu, He Nikolai, Perov School of Medicine and Health Harbin Institute of Technology Harbin China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China The First Affiliated Hospital of Harbin Medical University Harbin China National Center for Respiratory Medicine State Key Laboratory of Respiratory Health and Multimorbidity National Clinical Research Center for Respiratory Diseases Institute of Respiratory Medicine Chinese Academy of Medical Sciences Department of Pulmonary and Critical Care Medicine Center of Respiratory Medicine China-Japan Friendship Hospital Beijing China College of Science Sichuan Agricultural University Chengdu China The Fourth Affiliated Hospital of Harbin Medical University Harbin China Department of Ophthalmology The Second Hospital Jilin University Changchun China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China Department of Mathematics Imperial College London United Kingdom Department of Computer Science University of Warwick Coventry United Kingdom Magnetism Department Faculty of Physics Lomonosov Moscow State University Moscow Russia Harbin Medical University China

Learning from natural bacteria flagellum, we demonstrate a magnetic polymer multilayer conical microrobot that bestow the controllable propulsion upon external rotating magnetic field with uniform intensity. The magnetic microrobots were constructed by template-assisted Layer-by-Layer technique technique and subsequent functionalization of magnetic particle onto the big opening of the microrobots. Geometric variables of the polymer microrobots, such as the diameter and wall thickness, can be controlled by selection of porous template and layers of assembly. The microrobots perform controllable propulsion through the manipulation of magnetic field. The comparative analysis of the movement behavior reveals that the deformation of microrobots may attributed to the propulsion upon rotating magnetic field, which is similar as that of natural bacteria. The influence of actuation frequencies and frequencies on the velocity of the microrobots is studied. Such use of polymer polymer multilayer tubular micro/nanoarchitectures results in significant savings in the processing costs and provides a simple and cost-effective fabrication route for the mass production of magnetic polymer microrobots. © 2024, The Authors. All rights reserved.

关键词： Bacteria

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Robotic grasp detection using effective graspable feature selection and precise classification

Robotic grasp detection using effective graspable feature se...

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International Joint Conference on Neural Networks (IJCNN)

作者： Jiahao Zhang Miao Li Chenguang Yang School of Automation Science and Engineering South China University of Technology GuangZhou China Suzhou Institute of Wuhan University Wuhan University Suzhou China Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

It is necessary to implement real-time grasp detection in robotic grasping tasks. To this end, in this paper we propose a method for effective graspable feature selection and precise classification. In a robotic grasping scene, our method can effectively select graspable rectangles and further extract useful features from them to generate a feature set. A convolutional neural network (CNN) is then developed to score and classify the elements in the feature set. Finally, we compute the desired robotic grasp pose based on the graspable feature that gets the highest score. In the test phase the proposed CNN network achieves an accuracy of 96.5% on the Cornell Grasping Dataset. In real-world grasping experiments 105 frames per second (fps) for the object's grasp detection and a grasp success rate of 89.9% have been achieved with our method.

关键词： Feature extraction Grasping Robot sensing systems Grippers Machine learning Support vector machines

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MyoPS: A Benchmark of Myocardial Pathology Segmentation Combining Three-Sequence Cardiac Magnetic Resonance Images

arXiv

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arXiv 2022年

作者： Li, Lei Wu, Fuping Wang, Sihan Luo, Xinzhe Martín-Isla, Carlos Zhai, Shuwei Zhang, Jianpeng Liu, Yanfei Zhang, Zhen Ankenbrand, Markus J. Jiang, Haochuan Zhang, Xiaoran Wang, Linhong Arega, Tewodros Weldebirhan Altunok, Elif Zhao, Zhou Li, Feiyan Ma, Jun Yang, Xiaoping Puybareau, Elodie Oksuz, Ilkay Bricq, Stephanie Li, Weisheng Punithakumar, Kumaradevan Tsaftaris, Sotirios A. Schreiber, Laura M. Yang, Mingjing Liu, Guocai Xia, Yong Wang, Guotai Escalera, Sergio Zhuang, Xiahai School of Data Science Fudan University Shanghai China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Departament de Matemàtiques & Informàtica Universitat de Barcelona Barcelona Spain Computer Vision Center Universitat Autònoma de Barcelona Spain School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science and Engineering Northwestern Polytechnical University Xi'An China College of Electrical and Information Engineering Hunan University Changsha China National Engineering Laboratory for Robot Visual Perception and Control Technology Changsha China College of Physics and Information Engineering Fuzhou University Fuzhou China Comprehensive Heart Failure Center Wuerzburg University Hospitals Wuerzburg Germany School of Engineering University of Edinburgh Edinburgh United Kingdom School of Robotics Xi'an Jiaotong-Liverpool University Suzhou China Department of Electrical and Computer Engineering University of California Los Angeles United States Department of Radiology and Diagnostic Imaging University of Alberta Edmonton Canada Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecomm-Unications Chongqing China ImViA Laboratory Université Bourgogne Franche-Comté Dijon France Computer Engineering Department Istanbul Technical University Istanbul Turkey Le Kremlin-Bicêtre France Department of Mathematics Nanjing University of Science and Technology Nanjing China Department of Mathematics Nanjing University Nanjing China

Assessment of myocardial viability is essential in diagnosis and treatment management of patients suffering from myocardial infarction, and classification of pathology on myocardium is the key to this assessment. This work defines a new task of medical image analysis, i.e., to perform myocardial pathology segmentation (MyoPS) combining three-sequence cardiac magnetic resonance (CMR) images, which was first proposed in the MyoPS challenge, in conjunction with MICCAI 2020. The challenge provided 45 paired and pre-aligned CMR images, allowing algorithms to combine the complementary information from the three CMR sequences for pathology segmentation. In this article, we provide details of the challenge, survey the works from fifteen participants and interpret their methods according to five aspects, i.e., preprocessing, data augmentation, learning strategy, model architecture and post-processing. In addition, we analyze the results with respect to different factors, in order to examine the key obstacles and explore potential of solutions, as well as to provide a benchmark for future research. We conclude that while promising results have been reported, the research is still in the early stage, and more in-depth exploration is needed before a successful application to the clinics. Note that MyoPS data and evaluation tool continue to be publicly available upon registration via its homepage (***/zhuangxiahai/0/myops20/). © 2022, CC BY-NC-SA.

关键词： Magnetic resonance imaging

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Thermodynamics and protection of discrete time crystals

arXiv

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arXiv 2025年

作者： Cenedese, Gabriele Mister, Samuel T. Antezza, Mauro Benenti, Giuliano De Chiara, Gabriele Center for Nonlinear and Complex Systems Dipartimento di Scienza e Alta Tecnologia Università degli Studi dell’Insubria via Valleggio 11 Como22100 Italy Istituto Nazionale di Fisica Nucleare Sezione di Milano via Celoria 16 Milano20133 Italy Quantum Engineering Technology Labs and Quantum Engineering Centre for Doctoral Training H. H. Wills Physics Laboratory Department of Electrical and Electronic Engineering University of Bristol BristolBS8 1FD United Kingdom UMR 5221 CNRS Université de Montpellier MontpellierF- 34095 France Institut Universitaire de France 1 rue Descartes ParisF-75231 Cedex 05 France Física Teòrica: Informació i Fenòmens Quàntics Departament de Física Universitat Autònoma de Barcelona Bellaterra08193 Spain Centre for Quantum Materials and Technology School of Mathematics and Physics Queen’s University Belfast BelfastBT7 1NN United Kingdom

Discrete-Time Crystals (DTC) are a non-equilibrium phase of matter characterized by the breaking of time-translation symmetry in periodically driven quantum systems. In this work, we present a detailed thermodynamic analysis of DTCs in a one-dimensional spin-1/2 chain coupled to a thermal bath. We derive a master equation from the microscopic model, and we explore key thermodynamic quantities, such as work, heat, and entropy production. Our results reveal that the DTC signature inevitably decays in the presence of environmental noise, but we show that a periodic measurement scheme can mitigate the effects of decoherence, stabilizing the subharmonic oscillations of the DTC for extended periods. These findings provide insights into the robustness of time-crystalline phases and potential strategies for protecting them in experimental settings. © 2025, CC BY.

关键词： Thermolysis

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Obstacle induced stochastic tree for fast path planning

Obstacle induced stochastic tree for fast path planning

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2019 IEEE International Conference on Real-Time Computing and robotics, RCAR 2019

作者： Liu, Xiaofeng Li, Jinming Hu, Fang Yang, Chenguang College of IoT Engineering Hohai University Changzhou213022 China Changzhou Key Laboratory of Robotics and Intelligent Technology Changzhou213022 China Jiangsu Key Laboratory of Special Robots Changzhou213022 China School of Electromechanical and Automobile Engineerng Changzhou Vacational Institue of Engineering Changzhou213164 China Bristol Robotics Laboratory University of the West of England BristolBS16 1QY United Kingdom

ISBN: (纸本)9781728137261

Rapidly-Exploring Random Tree (RRT) has been extensively applied to robot navigation field as a fast and effective path planning method. Rapidly-Exploring Random Tree Star (RRT*), one of the extensions of RRT, outperforms other methods because it can approach the optimal path with the number of iterations increases. Nonetheless, as the number of sampling points increases, it takes too long to get an optimal path and the convergence speed slows dramatically for RRT and all its variants, since the range of sampling is the entire configuration space. In this paper, we propose a novel method of robot path planning in the global knowledge scenario: obstacle induced stochastic tree algorithm. This algorithm regards the center point in obstacles as the sampling point, which significantly reduces the sampling range then shorts the time for path planning. Simulation results demonstrate that our algorithm can find a feasible path at a rapid rate. Compared with RRT and its variants algorithms, the algorithm has better performance in both time and path cost. © 2018 IEEE

关键词： Motion planning

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Active interactions between animals and technology: biohybrid approaches for animal behaviour research

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Animal Behaviour 2025年 224卷

作者： Papadopoulou, M. Ball, M. Bartashevich, P. Burns, A.L.J. Chiara, V. Clark, M.A. Costelloe, B.R. Fele, M. French, F. Hauert, S. Heinrich, M.K. Herbert-Read, J.E. Hoitt, J. Ioannou, C.C. Landgraf, T. Matchette, S.R. Polverino, G. Sankey, D.W.E. Scott, D.M. Sridhar, V.H. Strömbom, D. Trianni, V. Vo-Doan, T.T. King, A.J. Department of Biosciences Faculty of Science and Engineering Swansea University Swansea United Kingdom Department of Biology Lafayette College Easton PA United States Institute for Theoretical Biology Department of Biology Humboldt-Universität zu Berlin Berlin Germany Cluster of Excellence ‘Science of Intelligence’ Berlin Germany Department Fish Biology Fisheries and Aquaculture Leibniz Institute of Freshwater Ecology and Inland Fisheries Berlin Germany Faculty of Life Sciences Albrecht Daniel Thaer-Institute of Agricultural and Horticultural Sciences Humboldt-Universität zu Berlin Berlin Germany Museum and Institute of Zoology Polish Academy of Science Warszawa Poland School of Biological Sciences University of Bristol Bristol United Kingdom School of Natural Sciences Macquarie University Sydney Australia Centre for the Advanced Study of Collective Behaviour University of Konstanz Konstanz Germany Department of Biology University of Konstanz Konstanz Germany Department of Collective Behavior Max Planck Institute of Animal Behavior Konstanz Germany School of Computing and Digital Media London Metropolitan University London United Kingdom Bristol Robotics Laboratory University of Bristol Bristol United Kingdom IRIDIA Université Libre de Bruxelles Brussels Belgium Department of Zoology University of Cambridge Cambridge United Kingdom Department of Mathematics and Computer Science Freie Universität Berlin Berlin Germany Department of Ecological and Biological Sciences University of Tuscia Viterbo Italy School of Natural and Environmental Science Newcastle University Newcastle upon Tyne United Kingdom Centre for Ecology and Conservation Faculty of Environment Science and Economy University of Exeter Penryn Campus Cornwall United Kingdom School of Animal Rural and Environmental Sciences Nottingham Trent University Nottingham United Kingdom Department for the Ecology of Animal Societies Max Planck Institute of Animal Behavior Konstanz Germany Ins

Biohybrid approaches (where living and engineered components are combined) provide new opportunities for advancing animal behaviour research and its applications. This review article and accompanying special issue explores how different types of novel technologies can be used in the field of animal behaviour from three perspectives: (1) comprehension, (2) application and (3) integration. Under the perspective of ‘comprehension,’ we present examples of how technologies like virtual animals or robots can be used in experimental settings to interact with living animals in a standardized manner. Such interactions can advance our understanding of fundamental topics such as mate choice, social learning and collective behaviour. Under ‘application,’ we investigate the potential for technologies to monitor, react and interact with animals in a variety of scenarios. For example, we discuss how drones can be used to keep large herbivores away from valuable crops and robotic predators to deter invasive species. Under ‘integration,’ we discuss possibilities for the coexistence of engineered and biological systems, augmenting the capacity or resilience of either or both components. Integration can be physical, for example, livestock can have sensors sit in their inner body for temperature monitoring, or within the environment, where sensors or robots monitor and interact with animals, such as a short-term earthquake forecasting method. Based upon these three themes, we discuss and classify existing biohybrid animal behaviour research, including the four articles included in our special issue. We also consider the ethics of this emerging field, highlight the advantages and potential issues associated with using technologies to create biohybrid systems and emphasize how such technologies can support the advancement of animal behaviour research. © 2025 The Author(s)

关键词： behavioural control behavioural monitoring biomimetic robotics ethorobotics interspecies interaction sensory integration

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Quantum Optical Metrology of Correlated Phase and Loss

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Physical Review Letters 2020年第14期124卷 140501-140501页

作者： Patrick M. Birchall Euan J. Allen Thomas M. Stace Jeremy L. O’Brien Jonathan C. F. Matthews Hugo Cable Quantum Engineering Technology Labs H. H. Wills Physics Laboratory and Department of Electrical & Electronic Engineering University of Bristol Bristol BS8 1FD United Kingdom Quantum Engineering Centre for Doctoral Training H. H. Wills Physics Laboratory and Department of Electrical & Electronic Engineering University of Bristol Tyndall Avenue Bristol BS8 1FD United Kingdom ARC Centre of Excellence for Engineered Quantum Systems School of Mathematics and Physics University of Queensland Saint Lucia Queensland 4072 Australia School of Physics University of Western Australia Perth 6009 Australia

Optical absorption measurements characterize a wide variety of systems from atomic gases to in vivo diagnostics of living organisms. Here we study the potential of nonclassical techniques to reduce statistical noise below the shot-noise limit in absorption measurements with concomitant phase shifts imparted by a sample. We consider both cases where there is a known relationship between absorption and a phase shift, and where this relationship is unknown. For each case we derive the fundamental limit and provide a practical strategy to reduce statistical noise. Furthermore, we find an intuitive correspondence between measurements of absorption and of lossy phase shifts, which both show the same analytical form for precision enhancement for bright states. Our results demonstrate that nonclassical techniques can aid real-world tasks with present-day laboratory techniques.

关键词： Quantum metrology Quantum optics Quantum sensing

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Adaptive impedance control with trajectory adaptation for minimizing interaction force

Adaptive impedance control with trajectory adaptation for mi...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Jing Luo Chenguang Yang Etienne Burdet Yanan Li School of Electrical and Information Engineering Changsha University of Science and Technology Changsha China Bristol Robotics Laboratory University of the West of England Bristol U.K. Department of Bioengineering Imperial College of Science Technology and Medicine London U.K. Department of Engineering and Design University of Sussex Brighton U.K.

ISBN: (数字)9781728160757

ISBN: (纸本)9781728160764

In human-robot collaborative transportation and sawing tasks, the human operator physically interacts with the robot and directs the robot's movement by applying an interaction force. The robot needs to update its control strategy to adapt to the interaction with the human and to minimize the interaction force. To this end, we propose an integrated algorithm of robot's trajectory adaptation and adaptive impedance control to minimize the interaction force in physical humanrobot interaction (pHRI) and to guarantee the performance of the collaboration tasks. We firstly utilize the information of the interaction force to regulate the robot's reference trajectory. Then, an adaptive impedance controller is developed to ensure automatic adaptation of the robot's impedance parameters. While one can reduce the interaction force by using either trajectory adaptation or adaptive impedance control, we investigate the task performance when combining both. Experimental results on a planar robotic platform verify the effectiveness of the proposed method.

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