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arXiv 2023年

作者： Chen, Kexin Li, Junyou Wang, Kunyi Du, Yuyang Yu, Jiahui Lu, Jiamin Li, Lanqing Qiu, Jiezhong Pan, Jianzhang Huang, Yi Fang, Qun Ann Heng, Pheng Chen, Guangyong Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Zhejiang Lab Hangzhou China Institute of Intelligent Chemical Manufacturing and iChemFoundry Platform ZJU-Hangzhou Global Scientific and Technological Innovation Center Hangzhou China Institute of Microanalytical Systems Department of Chemistry Zhejiang University Hangzhou China

Recent AI research plots a promising future of automatic chemical reactions within the chemistry society. This study proposes Chemist-X, a transformative AI agent that automates the reaction condition recommendation (RCR) task in chemical synthesis with retrieval-augmented generation (RAG) technology. To emulate expert chemists' strategies when solving RCR tasks, Chemist-X utilizes advanced RAG schemes to interrogate online molecular databases and distill critical data from the latest literature database. Further, the agent leverages state-of-the-art computer-aided design (CAD) tools with a large language model (LLM) supervised programming interface. With the ability to utilize updated chemical knowledge and CAD tools, our agent significantly outperforms conventional synthesis AIs confined to the fixed knowledge within its training data. Chemist-X considerably reduces chemists' workload and allows them to focus on more fundamental and creative problems, thereby bringing closer computational techniques and chemical research and making a remarkable leap toward harnessing AI's full capabilities in scientific discovery. Copyright © 2023, The Authors. All rights reserved.

关键词： Synthesis (chemical)

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Wheel-Terrain Contact Geometry Estimation using the Aside-Wheel RGB-D Sensor over Soft Terrain

Wheel-Terrain Contact Geometry Estimation using the Aside-Wh...

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robotics, Automation and Artificial Intelligence (RAAI), IEEE International Conference on

作者： Pengxuan Zhana Chen Yao Longteng Hu Feng Xue Peichen Wang Zheng Zhu Zhenzhong Jia Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen China Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology (SUSTech) Shenzhen China SUSTech Guang-dong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen China Harbin of Institute of Technology (HIT) Harbin China College of Engineering University of Michigan Ann Arbor Michigan USA School of Electronics Harbin Institute of Technology Harbin China

ISBN: (数字)9798350307566

ISBN: (纸本)9798350307573

Wheeled mobile robots (WMRs) have exhibited notable competitiveness in various applications, including geo-graphic and planetary exploration. Nonetheless, when traversing on soft terrains, their wheels might encounter sinkage and slippage, leading to mission failure. Consequently, real-time estimation of contact parameters such as sinkage and slip ratio holds significant importance for rover operations. In this paper, we introduce a novel algorithm that employs only one aside-wheel RGB-D camera for the simultaneous detection of wheel sinkage and slip ratio on deformable terrains in real-time. We estimate sinkage through the depth module by processing point cloud data, and we estimate slip ratio through the color module with a sequence of image processing steps. Utilizing only one single camera reduces errors arising from sensor signal alignment and enhances detection accuracy. With a single-wheel testbed, we simulate wheel motion under different slip ratios and carry out numerous experiments to validate the effectiveness of the proposed algorithm. Our algorithm attains a detection frequency of up to 20Hz and exhibits outstanding precision. The relative sinkage error remains below 4%, while the relative slippage error is confined within 0.8%.

关键词： Accuracy Image color analysis Robot vision systems Wheels Estimation Cameras Real-time systems

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Retrospective for the Dynamic Sensorium Competition for predicting large-scale mouse primary visual cortex activity from videos 38

Retrospective for the Dynamic Sensorium Competition for pred...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Turishcheva, Polina Fahey, Paul G. Vystrčilová, Michaela Hansel, Laura Froebe, Rachel Ponder, Kayla Qiu, Yongrong Willeke, Konstantin F. Bashiri, Mohammad Baikulov, Ruslan Zhu, Yu Ma, Lei Yu, Shan Huang, Tiejun Li, Bryan M. De Wulf, Wolf Kudryashova, Nina Hennig, Matthias H. Rochefort, Nathalie L. Onken, Arno Wang, Eric Ding, Zhiwei Tolias, Andreas S. Sinz, Fabian H. Ecker, Alexander S. Institute of Computer Science and Campus Institute Data Science University of Göttingen Germany Department of Neuroscience Center for Neuroscience and Artificial Intelligence Baylor College of Medicine HoustonTX United States Department of Ophthalmology Byers Eye Institute Stanford University School of Medicine StanfordCA United States Stanford Bio-X Stanford University StanfordCA United States Wu Tsai Neurosciences Institute Stanford University StanfordCA United States International Max Planck Research School for Intelligent Systems Tübingen Germany Institute for Bioinformatics and Medical Informatics Tübingen University Germany lRomul Russia Institute of Automation Chinese Academy of Sciences China Beijing Academy of Artificial Intelligence China The Alan Turing Institute United Kingdom School of Informatics University of Edinburgh United Kingdom Centre for Discovery Brain Sciences University of Edinburgh United Kingdom Simons Initiative for the Developing Brain University of Edinburgh United Kingdom Department of Electrical Engineering Stanford University StanfordCA United States Max Planck Institute for Dynamics and Self-Organization Göttingen Germany

Understanding how biological visual systems process information is challenging because of the nonlinear relationship between visual input and neuronal responses. Artificial neural networks allow computational neuroscientists to create predictive models that connect biological and machine vision. Machine learning has benefited tremendously from benchmarks that compare different models on the same task under standardized conditions. However, there was no standardized benchmark to identify state-of-the-art dynamic models of the mouse visual system. To address this gap, we established the SENSORIUM 2023 Benchmark Competition with dynamic input, featuring a new large-scale dataset from the primary visual cortex of ten mice. This dataset includes responses from 78,853 neurons to 2 hours of dynamic stimuli per neuron, together with behavioral measurements such as running speed, pupil dilation, and eye movements. The competition ranked models in two tracks based on predictive performance for neuronal responses on a held-out test set: one focusing on predicting in-domain natural stimuli and another on out-of-distribution (OOD) stimuli to assess model generalization. As part of the NeurIPS 2023 Competition Track, we received more than 160 model submissions from 22 teams. Several new architectures for predictive models were proposed, and the winning teams improved the previous state-of-the-art model by 50%. Access to the dataset as well as the benchmarking infrastructure will remain online at ***. © 2024 Neural information processing systems foundation. All rights reserved.

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SEMI-DERAINGAN: A NEW SEMI-SUPERVISED SINGLE IMAGE DERAINING

SEMI-DERAINGAN: A NEW SEMI-SUPERVISED SINGLE IMAGE DERAINING

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2021 IEEE International Conference on Multimedia and Expo, ICME 2021

作者： Wei, Yanyan Zhang, Zhao Wang, Yang Zhang, Haijun Zhao, Mingbo Xu, Mingliang Wang, Meng School of Computer Science and Information Engineering Hefei University of Technology China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology China Department of Computer Science Harbin Institute of Technology Shenzhen China Department of Electronic Engineering City University of Hong Kong Hong Kong School of Information Engineering Zhengzhou University China

ISBN: (纸本)9781665438643

Although supervised single image deraining (SID) have obtained impressive results, they still cannot obtain satisfactory results on real images for the weak generalization of rain removal capacity. In this paper, we mainly discuss the semi-supervised SID and propose a new GAN-based deraining network called Semi-DerainGAN, which can use both synthetic and real data in a uniform network based on two supervised and unsupervised processes. For this task, a semi-supervised rain streak learner termed SSRML sharing the same parameters of both processes is derived, which makes the real images contribute more rain streak information, so that the resulted model has a strong generalization power to the real SID task. We also contribute a new real-world rain image dataset called Real200 to alleviate the difference between both synthetic and real image domains. Extensive results on public datasets show that our model can obtain competitive results, especially on the real rain images. © 2021 IEEE computer Society. All rights reserved.

关键词： Rain

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Theoretical Model Construction of Deformation-Force for Soft Grippers Part II: Displacement Control Based Intrinsic Force Sensing

arXiv

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arXiv 2023年

作者： Dong, Huixu Zheng, Ziyi Guo, Haotian Yang, Sihao Qiu, Chen Dai, Jiansheng Chen, I. Ming Zhejiang University Hangzhou310058 China Robotics Research Center Nanyang Technological University Singapore639798 Singapore Maider Medical Industry Equipment Co. Itd 317607 China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems SUSTech Institute of Robotics Southern University of Science and Technology Shenzhen518055 China Centre for Robotics Research Department of Engineering King’s College London Strand LondonWC2R 2LS United Kingdom

Force-aware grasping is an essential capability for most robots in practical applications. Especially for compliant grippers, such as Fin-Ray gripper, it still remains challenging to build a bidirectional mathematical model that mutually maps the shape deformation and contact force. Part I of this article has constructed the force-displacement relationship for design optimization through the co-rotational theory. In Part II, we further devise a displacement-force mathematical model, enabling the compliant gripper to precisely estimate contact force from deformations sensor-free. The presented displacement-force model elaborately investigates contact forces and provides force feedback for a force control system of a gripper, where deformation appears as displacements in contact points. After-wards, simulation experiments are conducted to evaluate the performance of the proposed model through comparisons with the finite-element analysis (FEA) in Ansys. Simulation results reveal that the proposed model accurately estimates contact force, with an average error of around 3% and 4% for single or multiple node cases, respectively, regardless of various design parameters (Part I of this article is released in Arxiv1). Copyright © 2023, The Authors. All rights reserved.

关键词： Grippers

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Development of Virtual Learning Factory Toolkit for Production Engineering Education 13

Development of Virtual Learning Factory Toolkit for Producti...

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13th International DAAAM Baltic Conference and 29th International Baltic Conference, BALTMATTRIB 2021

作者： Mahmood, Kashif Otto, Tauno Kuts, Vladimir Terkaj, Walter Urgo, Marcello Haidegger, Geza Department of Mechanical and Industrial Engineering Tallinn University of Technology Tallinn Estonia STIIMA-CNR Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing National Research Council Milan Italy Manufacturing and Production Systems Division Department of Mechanical Engineering Politecnico di Milano Milan Italy SZTAKI – Institute for Computer Science and Control Budapest Hungary

The advent of industry 4.0 and the continuous digitalization of production ask for the enhancement of human skills and competences in the field of information and communication technology (ICT). Therefore, higher education has to keep pace with the global market needs for the necessary ICT skills and the overall understanding of the complexity of industries in 21st century. This paper focuses on the development and integration of Virtual Learning Factory (VLF) tools that can be used in production management and engineering education. The digital tools integrated in VLF toolkit can help students to exploit enabling technologies like simulation and virtual reality in their manufacturing studies and practical projects with industrial companies. © 2021 DAAAM International. All rights reserved.

关键词： Engineering education

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Constructive barrier feedback for collision avoidance in leader-follower formation control

arXiv

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arXiv 2023年

作者： Tang, Zhiqi Cunha, Rita Hamel, Tarek Silvestre, Carlos Institute for Systems and Robotics Instituto Superior Técnico Universidade de Lisboa Portugal Division of Decision and Control Systems KTH Royal Institute of Technology Sweden I3S-CNRS Université Côte d'Azur Institut Universitaire de France France Department of Electrical and Computer Engineering The Faculty of Science and Technology The University of Macau China

This paper proposes a novel constructive barrier feedback for reactive collision avoidance between two agents. It incorporates this feature in a formation tracking control strategy for a group of 2nd-order dynamic robots defined in three-dimensional space. Using only relative measurements between neighboring agents, we propose an elegant decentralized controller as the sum of a nominal tracking controller and the constructive barrier feedback for leader-follower formations under a directed single-spanning tree graph topology. The key ingredient is the use of divergent flow as a dissipative term, which slows down the relative velocity in the direction of the neighboring robots without compromising the nominal controller's performance. Compared to traditional barrier function-based optimization controllers, the proposed constructive barrier feedback avoids feasibility issues and results in more computationally efficient control algorithms with systematic equilibrium analysis. Simulations are provided to validate the effectiveness of the proposed control method. © 2023, CC BY-NC-ND.

关键词： Collision avoidance

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Reliability-Aware Network Slicing based on Multi-Objective Optimization

Reliability-Aware Network Slicing based on Multi-Objective O...

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Congress on Evolutionary Computation

作者： Qiqi Xia Jin Wang Chengqiang Huang Xin Yao Research Institute of Trustworthy Autonomous Systems (RITAS) Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Guangdong Key Laboratory of Brain-inspired Intelligent Computation Southern University of Science and Technology Shenzhen China Reliability Technology Lab Huawei Technologies Co. Ltd. Shenzhen China Department of Computing and Decision Sciences Lingnan University Hong Kong SAR China

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Network slicing is an essential technology in 5G and the forthcoming 6G networks. It aims to embed multiple virtual networks, i.e., network slices, on top of a shared substrate network to meet diverse service requirements. While a considerable body of existing research strives to maximize overall profits by meeting the resource demands of the network slices, optimizing their reliability is frequently overlooked. In this paper, we formalize the network slicing problem as a multi-objective optimization problem that aims to maximize total profits and reliability of network slices. To tackle this problem, we propose a new multi-objective optimization approach that improves over the state-of-the-art algorithm, which can achieve good approximate Pareto front results balancing total profits and reliability of network slices. The performance of our proposed method is evaluated on both artificial and real-world network topologies. Experimental results demonstrate the superior performance of our proposed method compared to the baseline algorithm, outperforming the latter in 92% of instances in terms of the Hypervolume (HV) metric.

关键词： Measurement 6G mobile communication Costs Network topology Network slicing Evolutionary computation Approximation algorithms

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Deep Learning Enables Large Depth-of-Field Images for Sub-Diffraction-Limit Scanning Superlens Microscopy

arXiv

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arXiv 2023年

作者： Sun, Hui Luo, Hao Wang, Feifei Chen, Qingjiu Chen, Meng Wang, Xiaoduo Yu, Haibo Zhang, Guanglie Liu, Lianqing Wang, Jianping Wu, Dapeng Li, Wen Jung Department of Mechanical Engineering City University of Hong Kong Hong Kong State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Department of Electrical and Electronics Engineering The University of Hong Kong Hong Kong Shenzhen518000 China Department of Computer Science City University of Hong Kong Hong Kong

Scanning electron microscopy (SEM) is indispensable in diverse applications ranging from microelectronics to food processing because it provides large depth-of-field images with a resolution beyond the optical diffraction limit. However, the technology requires coating conductive films on insulator samples and a vacuum environment. We use deep learning to obtain the mapping relationship between optical super-resolution (OSR) images and SEM domain images, which enables the transformation of OSR images into SEM-like large depth-of-field images. Our custom-built scanning superlens microscopy (SSUM) system, which requires neither coating samples by conductive films nor a vacuum environment, is used to acquire the OSR images with features down to ~80 nm. The peak signal-to-noise ratio (PSNR) and structural similarity index measure values indicate that the deep learning method performs excellently in image-to-image translation, with a PSNR improvement of about 0.74 dB over the optical super-resolution images. The proposed method provides a high level of detail in the reconstructed results, indicating that it has broad applicability to chip-level defect detection, biological sample analysis, forensics, and various other fields. Copyright © 2023, The Authors. All rights reserved.

关键词： Scanning electron microscopy

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Variation of sEMG with Muscle Fatigue for Lower Limb Stroke Patient During Walking

Variation of sEMG with Muscle Fatigue for Lower Limb Stroke ...

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IEEE International Conference on robotics and Biomimetics

作者： Wenze Shang Ruisen Huang Wei-Hsin Liao Xinyu Wu Fei Gao Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

sEMG signal is widely used and explored in control strategies of powered assistive human-robot interaction systems due to its non-invasive nature and ability to estimate motion intention well. However, prolonged use of the sEMG-based systems leads to muscle fatigue, contributing to unstable sEMG signals and regarding the performance of sEMG-based control strategies. In this study, three subjects, including two healthy subjects and one stroke subject, participated in our experiment, and the time domain, frequency domain, and complex features extracted from their $sEMG$ signals were utilized to evaluate muscle fatigue. The results indicate that $sEMG$ from the stroke side of the stroke subject contains more non-linear and chaotic parts, and the statistical differences between different trials are more significant, indicating that stroke has a more significant impact on the stroke side of the stroke subject. This study suggests that RMS in the stroke side of stroke subjects is less than that in others, whereas FuzzyEn in the stroke side of stroke subjects is greater than that in others, indicating that stroke leads to different motion patterns and more susceptibility to muscle fatigue.

关键词： Legged locomotion Limbs Frequency-domain analysis Biomimetics Human-robot interaction Muscles Fatigue Feature extraction Time-domain analysis Robots

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