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Toward a Novel Robotic Manta With Unique Pectoral Fins

IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2022年第3期52卷 1663-1673页

作者： Meng, Yan Wu, Zhengxing Dong, Huijie Wang, Jian Yu, Junzhi Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Peking Univ Coll Engn BIC ESATDept Adv Mfg & Robot State Key Lab Turbulence & Complex Syst Beijing 100871 Peoples R China

This article proposes the mechanical design and dynamic model of an innovative manta-inspired robot system for both efficient fast swimming and high spatial maneuverability. Inspired by some biological studies, a pair of unique pectoral fins with six separate degrees of freedoms (DOFs) are developed. The novel design is characterized by an improved crank-rocker mechanism and a distinctive horizontal DOF. The former not only endows the robot with high swimming speed, but also guarantees efficient flapping patterns which are close to manta rays. The latter is employed to coordinate with the flapping movement, allowing remarkable pitch adjustment. Further, the basic motion strategy is presented by detailed analyses to the pectoral fins. Besides, based on the Morrison equation and infinitesimal method, a complete dynamic model for robotic manta with flexible pectoral fins is established, whose parameters are determined through experimental data. Moreover, the linear swimming and pitching experiments are conducted, demonstrating the prominent movement performance of the presented design and the effectiveness of the dynamic model. The obtained results shed light on updated design and control of next-generation agile underwater vehicles and robots capable of multimodal motions in dynamic and complex aquatic environments.

关键词： Robots Robot kinematics Sports Vehicle dynamics Mathematical model Aerodynamics Prototypes Dynamic model pectoral fins robotic manta spatial maneuverability underwater robotics

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Parallel Sensing in Metaverses: Virtual-Real Interactive Smart systems for “6S” Sensing

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IEEE/CAA Journal of Automatica Sinica 2022年第12期9卷 2047-2054页

作者： Yu Shen Yuhang Liu Yonglin Tian Xiaoxiang Na School of Artificial Intelligence University of Chinese Academy of ScienceBeijing 100190China IEEE The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Department of Engineering University of CambridgeTrumpington StreetCB21PZUnited Kingdom

In the construction of Metaverses,sensors that are referred to as the“bridge of information transmission”,play a key *** functionality and efficiency of today’s sensors,which operate in a manner similar to physical sensing,are frequently constrained by their hardware and *** this research,we proposed the Parallel Sensing framework,which includes background,concept,basic methods and typical application of parallel *** our formulation,sensors are redefined as the integration of real physical sensors and virtual software-defined sensors based on parallel intelligence,in order to boost the performance of the *** sensor will have a parallel counterpart in the virtual world within the framework of parallel *** sensors serve as the brain of sensors and maintain the same properties as physical *** sensing allows physical sensors to operate in discrete time periods to conserve energy,while cloud-based descriptive,predictive,and prescriptive sensors operate continuously to offer compensation data and serve as *** better illustrate parallel sensing concept,we show some example applications of parallel sensing such as parallel vision,parallel point cloud and parallel light fields,both of which are designed by construct virtual sensors to extend small real data to virtual big data and then boost the performance of perception *** results demonstrate the effective of parallel sensing *** interaction between the real and virtual worlds enables sensors to operate actively,allowing them to intelligently adapt to various scenarios and ultimately attain the goal of“Cognitive,Parallel,Crypto,Federated,Social and Ecologic”6S sensing.

关键词： Parallel Sensing Parallel Intelligence CPSS Metaverses Virtual and Real Interaction “6S”Sensing.

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Framework and key Technologies for High-speed Railway Comprehensive Transport Hub 3

Framework and Key Technologies for High-speed Railway Compre...

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3rd IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2023

作者： Xiong, Gang Zhang, Wei Liu, Xiaoming Yuan, Zhiming Zhu, Fenghua Zhang, Zundong Chinese Academy of Sciences State Key Laboratory for Multimodal Artificial Intelligence Systems Beijing China North China University of Technology School of Electrical and Control Engineering Beijing China China Academy of Railway Science Communication Signal Research Institute Beijing China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China

ISBN: (纸本)9798350318470

The surge in urban population density in China has underscored the vital role of high-speed rail and subway systems in urban transit. Comprehensive transportation hubs, notably high-speed rail passenger terminals, have emerged as linchpins for seamless multimodal transit both within and beyond urban centers. China's railway sector vigorously champions the innovative concept of "station-city integration"and has articulated a forward-looking "16-word policy"for modern railway stations: "Seamless integration, environmental friendliness, economic viability, and intelligent accessibility". The judicious allocation of resources and the augmentation of coordination and control capabilities within comprehensive transportation hubs are imperative for the harmonious evolution of urban transit. The implementation of intelligent control systems for transportation hubs has emerged as a pivotal area of research. This study delves into the framework and critical technologies for high-speed railway comprehensive transport hubs, encompassing various components and their intricate interplay, including transport modalities, infrastructure, travelers, environmental factors, and information systems, thus forming a prototypical cyber-physical-social system. Addressing the prevalent and pressing imperative for the advancement of "station-city integration"high-speed railway comprehensive transport hubs, this research endeavor aims to surmount bottleneck challenges and refine the oversight of passenger flows at high-speed rail terminals. The findings hold noteworthy theoretical import and portend promising practical applications. © 2023 IEEE.

关键词： Integration

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Parallel Learning Based Foundation Model for Networked Traffic Signal control 26

Parallel Learning Based Foundation Model for Networked Traff...

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IEEE 26th International Conference on Intelligent Transportation systems (ITSC)

作者： Zhao, Chen Dai, Xingyuan Chen, Yuanyuan Lin, Yilun Lv, Yisheng Wang, Fei-Yue Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Shanghai AI Lab Shanghai 200232 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Macao Inst Syst Engn Macau 999078 Peoples R China

ISBN: (纸本)9798350399462

Networked Traffic Signal control (NTSC) is a fundamental component of Intelligent Transportation systems (ITS) and the broader vision of smart city development. While a plethora of intelligent strategies have been developed, the Sim2Real challenge often impedes their full realization. In response, this paper introduces the Parallel Learning-based Adaptive Network for Traffic Signal control (PLANT) as a foundation model for NTSC. We employ the Wasserstein GAN with Gradient Penalty (WGAN-GP) to generate a wide range of artificial scenarios for robust PLANT training. Further, the Transformer-based Cooperation Mechanism (TCM) is integrated as the primary learner within PLANT, facilitating effective capture of traffic dynamics and knowledge accumulation. This knowledge is readily transferable to real-world applications through meticulous fine-tuning, equipping PLANT to adapt and evolve in alignment with shifting transportation paradigms. Our empirical study on the Hangzhou road network demonstrates PLANT's superiority over both traditional and emerging DRL-based approaches, emphasizing its viability as a potential foundation model for NTSC.

关键词： Intelligent systems

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Gliding Motion Optimization for a Biomimetic Gliding Robotic Fish

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2022年第3期27卷 1629-1639页

作者： Dong, Huijie Wu, Zhengxing Meng, Yan Tan, Min Yu, Junzhi Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Peking Univ Coll Engn State Key Lab Turbulence & Complex Syst BIC ESATDept Adv Mfg & Robot Beijing 100871 Peoples R China

In this article, we present a gliding efficiency optimization strategy based on deep reinforcement learning for a gliding robotic fish. For the gliding motion in shallow waters, the nonsteady motion strongly impacts the gliding range and also reduces efficiency. This article presents a concept of transient gliding motion and illustrates its importance for the gliding robotic fish. For better gliding performance of active fins, several pectoral fins with different sizes are designed and their hydrodynamics and optimizing capabilities are analyzed by computational fluid dynamics simulation. Then, a double deep Q network-based optimization strategy is proposed to improve gliding efficiency by active pectoral fins, in which an adversarial model and a two-stage reward function are presented for the adequate calculation of gliding range. Simulations are conducted to validate the convergence and effectiveness of the proposed strategy. The aquatic experiments are carried out to further verify the proposed strategy. The results reveal that the optimization strategy can save about 4.88% of energy and 19.45% of travel time. This article provides clues to the design of active control surfaces and improvement of gliding efficiency for underwater vehicles. Remarkably, the proposed strategy can significantly improve the duration and endow the robot with the potential to perform complex tasks.

关键词： Robots Optimization Buoyancy Transient analysis Robot kinematics Hydrodynamics Energy consumption Biomimetic robot deep reinforcement learning (DRL) gliding efficiency gliding robotic fish underwater robotics

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A Passive Compliance Obstacle-Crossing Robot for Power Line Inspection and Maintenance

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IEEE ROBOTICS AND AUTOMATION LETTERS 2023年第5期8卷 2772-2779页

作者： Chen, Minghao Cao, Yinghua Tian, Yunong Li, En Liang, Zize Tan, Min Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Chinese Acad Sci Engn Lab Ind Vis & Intelligent Equipment Technol Beijing 100190 Peoples R China

In scenarios of the overhead power line system, manual methods are inefficient and unsafe. Meanwhile, the majority of cantilevered robots have poor efficiency when crossing obstacles. This letter proposes a novel power line inspection and maintenance robot to solve these problems. The robot employs a passive compliance obstacle-crossing principle, which could rapidly cross obstacles with the cooperation of gas springs and climbing wheels. Under high payload, the robot could take 5-15 seconds without any complex strategies to roll over obstacles. A variable configuration platform is also designed, which has a multiple line mode and a single line mode. It makes the robot suitable for different kinds of overhead power lines. Meanwhile, the related adaptability analyses are presented. Manipulators are also installed to help the robot perform specific maintenance tasks. The results of lab experiments and field tests reveal that the robot could stably and rapidly cross obstacles, such as suspension clamps, vibration dampers, and spacers, and could perform three kinds of maintenance tasks on the line.

关键词： Robots Wheels Mobile robots Maintenance engineering Inspection Clamps Task analysis Power line inspection robot mechanical design telerobotics field robotics maintenance tasks

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Effect of sintering aids on mechanical properties and microstructure of alumina ceramic via stereolithography

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CERAMICS INTERNATIONAL 2023年第11期49卷 17506-17523页

作者： Qian, Chuchu Hu, Kehui Shen, Zhen Wang, Qing Li, Peijie Lu, Zhigang Tsinghua Univ State Key Lab Tribol Beijing 100084 Peoples R China Tsinghua Univ Dept Mech Engn Beijing 100084 Peoples R China Tsinghua Univ Minist Educ Key Lab Adv Mat Proc Technol Beijing 100084 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Ten Dimens Guangdong Technol Co Ltd Foshan 528225 Peoples R China

In this study, the effects of sintering aids (CaO, TiO2, La2O3 and ZrO2) on the physical and mechanical properties and microstructure of alumina ceramics made by stereolithography were systematically investigated. The addition of 3% CaO promoted internal porous structure at high temperatures, increasing the possibility of interlayer microcracking along the inner pores. 0.5% TiO2 had the best bending strength enhancement of alumina, increasing from 110.4 MPa to 201.1 MPa at a sintering temperature of 1650 degrees C. La2O3 took effect after 1550 degrees C and basically had no effect on refining grains. 1% ZrO2 increased 15% apparent porosity and 88% interlayer shear strength and reduced sintering shrinkage by about 30%, while maintaining bending strength. Optimised alumina powder ingredients and sintering conditions that could meet the performance index requirements of the ceramic core were obtained: particle size distribution 10 mu m/2 mu m (the mass fraction ratio of coarse to fine particles was 6:4), solid content 55%, sintering aid 1% ZrO2, sintering temperature 1450 degrees C.

关键词： Stereolithography Alumina additive manufacturing Sintering aids Mechanical properties Microstructure

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A Tight Filtering and Smoothing Fusion Method With Feature Tracking for LiDAR Odometry

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IEEE SENSORS JOURNAL 2022年第13期22卷 13622-13631页

作者： Liang, Shuang Cao, Zhiqiang Yu, Junzhi Tan, Min Wang, Shuo Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Peking Univ Coll Engn Dept Mech & Engn Sci BIC ESATState Key Lab Turbulence & Complex Syst Beijing 100871 Peoples R China

LiDAR odometry (LO) has gained popularity in recent years because of its growing applications. Existing solutions include filtering and smoothing, where the former optimizes the latest pose with high efficiency and the latter optimizes multiple poses with strong consistency. Still, it is promising to fuse filtering and smoothing in LO. In this paper, we propose a novel tight filtering and smoothing fusion method. Firstly, two nested sliding windows are maintained and they share estimated poses and features to balance the accuracy and efficiency. The large outer window is used to build a large local map for high-quality scan-to-map matching in the filtering module, and multiple poses in the small inner window are optimized in the smoothing module to improve local consistency and efficiency. Furthermore, sparse directed geometry points (DGPs) are tracked across window keyframes to produce feature-wise multiple residuals for poses optimization in both filtering and smoothing modules. Besides, the strategies of ratio-based refined pose optimization and efficient DGP feature triangulation are developed for pose refinement and local map update, respectively. The experiments on KITTI and Newer College (NC) datasets demonstrate the effectiveness of the proposed method.

关键词： Smoothing methods Feature extraction Filtering Laser radar Optimization Global Positioning System Point cloud compression LiDAR sensor LiDAR odometry filtering smoothing sliding window

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Feature-guided attention network for medical image segmentation

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MEDICAL PHYSICS 2023年第8期50卷 4871-4886页

作者： Zhou, Hao Sun, Chaoyu Huang, Hai Fan, Mingyu Yang, Xu Zhou, Linxiao Harbin Engn Univ Natl Key Lab Sci & Technol Underwater Vehicle Harbin Peoples R China Harbin Med Univ Affiliated Hosp 4 Harbin Peoples R China Wenzhou Univ Coll Comp Sci & Artificial Intelligence Wenzhou Peoples R China Chinese Acad Sci Inst Automation State Key Lab Management & Control Complex Syst Beijing Peoples R China

BackgroundU-Net and its variations have achieved remarkable performances in medical image segmentation. However, they have two limitations. First, the shallow layer feature of the encoder always contains background noise. Second, semantic gaps exist between the features of the encoder and the decoder. Skip-connections directly connect the encoder to the decoder, which will lead to the fusion of semantically dissimilar feature maps. PurposeTo overcome these two limitations, this paper proposes a novel medical image segmentation algorithm, called feature-guided attention network, which consists of U-Net, the cross-level attention filtering module (CAFM), and the attention-guided upsampling module (AUM). MethodsIn the proposed method, the AUM and the CAFM were introduced into the U-Net, where the AUM learns to filter the background noise in the low-level feature map of the encoder and the CAFM tries to eliminate the semantic gap between the encoder and the decoder. Specifically, the AUM adopts a top-down pathway to use the high-level feature map so as to filter the background noise in the low-level feature map of the encoder. The AUM uses the encoder features to guide the upsampling of the corresponding decoder features, thus eliminating the semantic gap between them. Four medical image segmentation tasks, including coronary atherosclerotic plaque segmentation (Dataset A), retinal vessel segmentation (Dataset B), skin lesion segmentation (Dataset C), and multiclass retinal edema lesions segmentation (Dataset D), were used to validate the proposed method. ResultsFor Dataset A, the proposed method achieved higher Intersection over Union (IoU) (67.91 +/- 3.82%$67.91\pm 3.82\%$), dice (79.39 +/- 3.37%$79.39\pm 3.37\%$), accuracy (98.39 +/- 0.34%$98.39\pm 0.34\%$), and sensitivity (85.10 +/- 3.74%$85.10\pm 3.74\%$) than the previous best method: CA-Net. For Dataset B, the proposed method achieved higher sensitivity (83.50%) and accuracy (97.55%) than the previous best metho

关键词： attention-guided upsampling module cross-level attention filtering module medical image segmentation

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Robot Navigation Based on Situational Awareness

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IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL systems 2022年第3期14卷 869-881页

作者： Liu, Xilong Cao, Zhiqiang Yu, Yingying Ren, Guangli Yu, Junzhi Tan, Min Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Peking Univ State Key Lab Turbulence & Complex Syst Dept Mech & Engn Sci BIC ESATColl Engn Beijing 100871 Peoples R China

Autonomous navigation for mobile robots is a prerequisite to complete the tasks. In this article, we propose a novel navigation method based on situational awareness. The scene predictor, scene interpreter and the topological map-based planner are the main components, where the scene interpreter is used to realize the mapping of perception information, and the scene predictor predicts the information in the neighborhood of current position. The basic idea of this research is the feeling of path. Based on the definitions of path and the amount of perception, the situational awareness fitting network is designed as the scene interpreter, and the position of the robot in a path can be implicitly described by a situational awareness value. With the global guidance of the planner, the robot achieves navigation. The proposed navigation method does not rely on Cartesian-based global position and its effectiveness is verified by simulations and experiments.

关键词： Navigation Robots Robot sensing systems Fitting Sensors Computational modeling Three-dimensional displays Path perception robot navigation situational awareness fitting network

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