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International Conference on Communication Engineering and Technology (ICCET)

作者： Mo Guan Liangliang Qi Xi Jin Suoling Guan Changqing Xia Chi Xu Shenyang University of Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China

Digital oilfields generally adopt the multi-hop technology to expand the network scale, and the data generated depends on the large-scale wireless sensor network (WSN) for transmission. However, multi-hop communication will lead to uneven distribution of network energy consumption and premature death of nodes. To prolong the network lifetime of digital oilfields, we extended the narrowband internet of things (NB-IoT) module on some WSN nodes deployed on site to form heterogeneous nodes. Through the heterogeneity of NB-IoT and WSN, the nodes could transmit as little data as possible from other nodes, fundamentally reducing the node energy consumption. Furthermore, an optimization method was proposed that could simultaneously optimize the network lifetime and node expansion cost. The experimental results revealed that the proposed algorithm could greatly prolong the network lifetime while only introducing a small number of nodes.

关键词： Wireless sensor networks Energy consumption Costs Optimization methods Spread spectrum communication Internet of Things Narrowband

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MuST: Maximizing the Latent Capacity of Spatial Transcriptomics Data with Multi-modality Structure Transformation

MuST: Maximizing the Latent Capacity of Spatial Transcriptom...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Zelin Zang Liangyu Li Yongjie Xu Jiahao Li Chenrui Duan Yi Sun Zhen Lei Stan Z. Li Centre for Artificial Intelligence and Robotics (CAIR) HKISI-CAS AI Lab Research Center for Industries of the Future Westlake University Hangzhou State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS) Institute of Automation Chinese Academy of Sciences (CASIA) School of Artificial Intelligence University of Chinese Academy of Sciences (UCAS)

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Spatial transcriptomics (ST) technologies have revolutionized the study of gene expression patterns in tissues by providing multimodality data in transcriptomic, spatial, and morphological, offering opportunities for understanding tissue biology beyond transcriptomics. However, we identify the modality bias phenomenon in ST data species, i.e., the inconsistent contribution of different modalities to the labels leads to a tendency for the analysis methods to retain the information of the dominant modality. How to mitigate the adverse effects of modality bias to satisfy various downstream tasks remains a fundamental challenge. This paper introduces Multiple-modality Structure Transformation, named MuST, a novel methodology to tackle the challenge. MuST integrates the multi-modality information contained in the ST data effectively into a uniform latent space to provide a foundation for all the downstream tasks. It learns intrinsic local structures by topology discovery strategy and topology fusion loss function to solve the inconsistencies among different modalities. Thus, these topology-based and deep learning techniques provide a solid foundation for a variety of analytical tasks while coordinating different modalities. The effectiveness of MuST is assessed by performance metrics and biological significance. The results show that it outperforms existing state-of-the-art methods with clear advantages in the precision of identifying and preserving structures of tissues and biomarkers. MuST offers a versatile toolkit for the intricate analysis of complex biological systems. The code is available at https://***/zangzelin/code_Must.

关键词： Analytical models Biological system modeling Transcriptomics Biological tissues Spatial databases Data models Trajectory Topology Gene expression Biological information theory

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Trajectory planning of a manipulator based on the DDPG algorithm

Trajectory planning of a manipulator based on the DDPG algor...

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2022 International Workshop on automation, Control, and Communication Engineering, IWACCE 2022

作者： Jing, Xiangyu Zang, Chuanzhi Liu, Yuqi Liu, Yu Xia, Changqing Shenyang University of Technology No. 111 Shenliao West Road Economic and Technological Development Zone Shenyang110870 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9781510660915

Trajectory planning is one of the key technologies in the manipulator motion system, and the effectiveness of the manipulator as a whole is directly influenced by this technology. Thus, accurate and effective trajectory planning is crucial. In this study, a reinforcement learning system is used to plan a manipulator's trajectory. A trajectory planning of a manipulator based on the deep deterministic policy gradient (DDPG) method, which is easier to converge on than the Actor-Critic (AC) approach, is proposed in order to address the issue that the AC algorithm is difficult to converge on. A guiding reward function is provided in the reward function area to address the issue that the manipulator can't contact the target rapidly due to blind exploration. This can help the manipulator touch the target more quickly. In this paper, a twodegree of freedom manipulator is selected as the experimental object. The obstacle avoidance reward function based on the AC algorithm, the obstacle avoidance reward function based on the DDPG algorithm, and the obstacle avoidance reward function and guiding reward function based on the DDPG algorithm are compared. The findings demonstrate that the DDPG method converges easier than the AC algorithm, and that the directed reward function can help the manipulator avoid obstacles. © 2022 SPIE. All rights reserved.

关键词： Manipulators

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Reconfigurable Magnetic Microswarm for Thrombolysis under Ultrasound Imaging

Reconfigurable Magnetic Microswarm for Thrombolysis under Ul...

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2020 IEEE International Conference on robotics and automation, ICRA 2020

作者： Wang, Qianqian Wang, Ben Yu, Jiangfan Schweizer, Kathrin Nelson, Bradley J. Zhang, Li Department of Mechanical and Automation Engineering Shatin NT Hong Kong Eth Zurich Institute of Robotics and Intelligent Systems Zurich Switzerland

ISBN: (纸本)9781728173955

We propose thrombolysis using a magnetic nanoparticle microswarm with tissue plasminogen activator (tPA) under ultrasound imaging. The microswarm is generated in blood using an oscillating magnetic field and can be navigated with locomotion along both the long and short axis. By modulating the input field, the aspect ratio of the microswarm can be reversibly tuned, showing the ability to adapt to different confined environments. Simulation results indicate that both in-plane and out-of-plane fluid convection are induced around the microswarm, which can be further enhanced by tuning the aspect ratio of the microswarm. Under ultrasound imaging, the microswarm is navigated in a microchannel towards a blood clot and deformed to obtain optimal lysis. Experimental results show that the lysis rate reaches -0.1725 ± 0.0612 mm3/min in the 37C blood environment under the influence of the microswarm-induced fluid convection and tPA. The lysis rate is enhanced 2.5-fold compared to that without the microswarm (-0.0681 ± 0.0263 mm3/min). Our method provides a new strategy to increase the efficiency of thrombolysis by applying microswarm-induced fluid convection, indicating that swarming micro/nanorobots have the potential to act as effective tools towards targeted therapy. © 2020 IEEE.

关键词： Aspect ratio

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LOCAL-PROMPT: EXTENSIBLE LOCAL PROMPTS FOR FEW-SHOT OUT-OF-DISTRIBUTION DETECTION

arXiv

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arXiv 2024年

作者： Zeng, Fanhu Cheng, Zhen Zhu, Fei Wei, Hongxin Zhang, Xu-Yao State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China Centre for Artificial Intelligence and Robotics HKISI-CAS Hong Kong Department of Statistics and Data Science Southern University of Science and Technology China

Out-of-Distribution (OOD) detection, aiming to distinguish outliers from known categories, has gained prominence in practical scenarios. Recently, the advent of vision-language models (VLM) has heightened interest in enhancing OOD detection for VLM through few-shot tuning. However, existing methods mainly focus on optimizing global prompts, ignoring refined utilization of local information with regard to outliers. Motivated by this, we freeze global prompts and introduce Local-Prompt, a novel coarse-to-fine tuning paradigm to emphasize regional enhancement with local prompts. Our method comprises two integral components: global prompt guided negative augmentation and local prompt enhanced regional regularization. The former utilizes frozen, coarse global prompts as guiding cues to incorporate negative augmentation, thereby leveraging local outlier knowledge. The latter employs trainable local prompts and a regional regularization to capture local information effectively, aiding in outlier identification. We also propose regional-related metric to empower the enrichment of OOD detection. Moreover, since our approach explores enhancing local prompts only, it can be seamlessly integrated with trained global prompts during inference to boost the performance. Comprehensive experiments demonstrate the effectiveness and potential of our method. Notably, our method reduces average FPR95 by 5.17% against state-of-the-art method in 4-shot tuning on challenging ImageNet-1k dataset, even outperforming 16-shot results of previous methods. Code is released at https://***/AuroraZengfh/Local-Prompt. Copyright © 2024, The Authors. All rights reserved.

关键词： Visual languages

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Design Considerations of Outer-Rotor Flux-Modulated Permanent-Magnet In-Wheel Motors

Design Considerations of Outer-Rotor Flux-Modulated Permanen...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Zekang Huang Yixiao Luo Wenyuan Mi Zheng Cai Fei Zhao Hang Zhao Jincheng Yu School of Mechanical Engineering and Automation Harbin Institute of Technology (Shenzhen) Shenzhen China School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China Robotics and Autonomous Systems Thrust Hong Kong University of Science and Technology (Guangzhou) Guangzhou China

This paper presents the design considerations of outer-rotor flux-modulated permanent-magnet (OR-FMPM) in-wheel motors applied to light electric vehicles (EVs). The basic wheel model and drive system specifications are considered in the motor design, with utility of the flat-wire armature windings. The multi-step motor optimization focusing on the outer-rotor PM machines is carried out to reach the design objectives of the drive system, with auxiliary of the sensitivity analysis to lower the computing burden. Finally, the motor electromagnetic performances are specifically analyzed, verifying the feasibility of the motor design in the application of in-wheel motors.

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Feasibility Investigation on Sinusoidal-Reluctance Rotor Contour in Variable Reluctance Resolver

Feasibility Investigation on Sinusoidal-Reluctance Rotor Con...

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Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： Wenyuan Mi Jincheng Yu Zheng Cai Hang Zhao Fei Zhao Yixiao Luo School of Mechanical Engineering and Automation Harbin Institute of Technology (Shenzhen) Shenzhen China Robotics and Autonomous Systems Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China

In this digest, a novel variable reluctance (VR) resolver with sinusoidal-reluctance rotor contour is proposed and its envelope feasibility is evaluated via the analytical and finite element (FE) analysis. Moreover, the third order harmonic suppression via flux leakage compensation is addressed to reveal the operation principle of the proposed VR resolver. Under 4 mm tooth width, the total harmonic distortion of the cosine envelope with the proposed rotor contour can be limited to only 0.56%.

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Backstepping-Based Adaptive Cooperative Control For Multiple Euler-Lagrange systems Under Unknown Harmonic Disturbances

Backstepping-Based Adaptive Cooperative Control For Multiple...

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Chinese automation Congress (CAC)

作者： Ying Chen Zi-Yi Zhao Peng Sun Xiang-Gui Guo Jian-Liang Wang Daniel Coutinho Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Collaborative Flying Robotics Hangzhou Innovation Institute of Beihang University HangZhou China Department of Automation and Systems Universidade Federal de Santa Catarina Florianópolis Brazil

This paper studies cooperative control problem for multiple Euler-Lagrange systems with unknown harmonic disturbances, where the disturbances are the superposition of sinusoidal components with unknown amplitude, phase, and frequency. A novel adaptive disturbance observer without requiring the disturbance frequency information is designed to estimate the disturbances. Over the directed network topology, a cooperative control scheme is proposed based on backstepping techniques, so that the tracking error is ultimately uniformly bounded. The scheme developed can be used to reject the harmonic disturbances in a uniform way, which means the characteristics of the disturbances can be described as a fixed parameter vector. Finally, an application is presented to demonstrate the effectiveness of the proposed control strategy in the context of a two-link manipulator system.

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Field Experiments with an Automated Utility Platform for Transportation and Work Processes

Field Experiments with an Automated Utility Platform for Tra...

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IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Raimund Edlinger Stefan Dumberger Roman Froschauer Wolfgang Pointner Marcel Zeilinger Andreas Nü chter Smart Automation and Robotics University of Applied Sciences Upper Austria Wels Austria Assistive &#x0026 Autonomous Systems AIT &#x2013 Austrian Institute of Technology Vienna Austria Informatics VII - Robotics and Telematics Julius-Maximilians-University W&#x00FC rzburg W&#x00FC rzburg Germany

The automation of transport and work tasks in various application domains continues to be a major challenge. The proposed paper presents key technologies within a process from sensing to reasoning and includes: (i) understanding the scene and its relations through new approaches in object classification and pose estimation based on machine learning, as well as methods for reliable detection of objects and object features; (ii) reliable and safe outdoor localization and mapping based on multi-modal approaches and innovative camera-based methods. The fusion of different sensor data is used for reliable obstacle detection and collision avoidance. The investigation of suitable system architectures, data processing platforms and communication mechanisms taking into account safety requirements is a prerequisite for the operation in a safety-critical environment. The paper provides a proof of concept for an automated platform to demonstrate and evaluate application scenario provided by the Linz Airport in the form of an automated transport process for air freight between a terminal and the aircraft.

关键词： Navigation Transportation systems architecture Switches Robot sensing systems Software Software reliability

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Design and Implementation of OpenWSN Hardware Platform

Design and Implementation of OpenWSN Hardware Platform

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Algorithms, High Performance Computing and Artificial Intelligence (AHPCAI), International Conference on

作者： Shusheng Zhang Chuang Xie Jun Liu Chun Zhao Zhijia Yang Jizhi Mao College of Automation and Electrical Engineering Shenyang Ligong University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

This paper proposes a new wireless sensor network hardware platform based on OpenWSN project launched by the University of California, Berkeley. The hardware platform's processor uses a 32-bit microcontroller (STM32F103RCT6) produced by STMicroelectronics (ST), and the wireless module uses the WISA470 chip. The final experimental results show that this platform can support the Open WSN project very well.

关键词： Wireless communication Radio frequency Wireless sensor networks Protocols Power supplies Microcontrollers Hardware

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