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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2024年第3期9卷 4240-4243页

作者： Yu, Hui Liang, Wei Fan, Lili Wang, Yutong Wang, Fei-Yue Univ Portsmouth Sch Creat Technol Portsmouth PO1 2DJ England Univ Shanghai Sci & Technol Shanghai 200093 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Beijing Inst Technol Sch Informat & Elect Beijing 100811 Peoples R China

Artificial technologies have made rapid progress and achieved various superior tasks in the past few years, including but not limited to classification, detection, image generation and data processing. Particularly, the very recent emerging Sora has demonstrated the exceptional ability of text-to-video generation lasting for 1 minute long with impressive quality. It provides a huge potential for many new applications across industries, especially social interaction in intelligent vehicles. The emergence of innovative intelligence vehicle applications has given rise to novel requirements for social and human-vehicle interaction within the associated contexts, where Sora and social vision could play an important role. In this perspective, we present a new Social Interaction framework based on Sora and parallel intelligence in intelligent vehicles and provide a novel perspective for conducting new social and human-vehicle interaction in the context of intelligent vehicles.

关键词： Intelligent vehicles Computational modeling Transformers Computer vision Visualization Human-vehicle systems Human computer interaction Sora parallel intelligence social vision social interaction intelligent Vehicles diffusion model human-machine interaction

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Covariance Estimation for Pose Graph Optimization in Visual-Inertial Navigation systems

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2023年第6期8卷 3657-3667页

作者： Shi, Pengcheng Zhu, Zhikai Sun, Shiying Rong, Zheng Zhao, Xiaoguang 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 NIO Inc Shanghai 201804 Peoples R China Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100190 Peoples R China

Pose graph optimization helps reduce drift accumulated in pure odometry of visual simultaneous localization and mapping (SLAM) systems by solving a nonlinear least square problem, including both sequential constraints and loop-closing constraints. However, the covariances of all constraints are set to constant matrices or by manual setting. In this paper, we propose a novel approach to approximate covariances of constraints in pose graph optimization to better represent the true uncertainty of the underlying visual-inertial navigation system (VINS) that fuses inertial measurements and visual observations. Specifically, for sequential constraints, we propose to utilize nonlinear factor recovery to optimally extract covariance matrices from the accumulated visual-inertial odometry (VIO). For loop-closing constraints, we propose a dynamic scale estimation method to approximate the scales of the information matrices. To evaluate the effectiveness and robustness of the proposed method, we conduct extensive experiments on public and self-collected datasets in various environments. Results show that our proposed method achieves higher accuracy compared with naively-formulated pose graph optimization adopted by several state-of-the-art visual-inertial navigation systems.

关键词： Covariance estimation loop closing pose graph optimization visual-inertial odometry

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LLM-Based Operating systems for Automated Vehicles: A New Perspective

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2024年第4期9卷 4563-4567页

作者： Ge, Jingwei Chang, Cheng Zhang, Jiawei Li, Lingxi Na, Xiaoxiang Lin, Yilun Li, Li Wang, Fei-Yue Tsinghua Univ Dept Automat BNRist Beijing 100084 Peoples R China Indiana Univ Purdue Univ Indianapolis Dept Elect & Comp Engn Indianapolis IN 46202 USA Univ Cambridge Dept Engn Cambridge CB2 1TN England Shanghai AI Lab Shanghai 200232 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

The deployment of large language models (LLMs) brings challenges to intelligent systems because its capability of integrating large-scale training data facilitates contextual reasoning. This paper envisions a revolution of the LLM based (Artificial) Intelligent Operating systems (IOS, or AIOS) to support the core of automated vehicles. We explain the structure of this LLM-OS and discuss the resulting benefits and implementation difficulties.

关键词： Operating systems Task analysis Software Hardware Cognition Safety Memory management Automated vehicles LLM operating system

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SynPoses: Generating Virtual Dataset for Pedestrian Detection in Corner Cases

IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION

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IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION 2022年 6卷 801-804页

作者： Nie, Yunhao Lu, Bo Chen, Qiyuan Miao, Qinghai Lv, Yisheng 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

Pedestrian detection based on deep learning methods makes a big hit during these days. The key to achieve excellent results for deep learning-based pedestrian detection methods is a high-quality dataset. There are lots of outstanding datasets for pedestrian detection like EuroCity Persons, CityPersons, Caltech, etc. However, their efforts are not dedicated to the traffic scenarios with pedestrians in various poses. When the state-of-the-art detectors trained on datasets described above encounter the scene with pedestrians in variously complicated poses, the results are mostly worse than expected. In order to alleviate this problem, we propose a framework called SynPoses to create synthetic human with complicated poses in high quality. Experimental results show that, when facing scenarios with human in diverse poses, the performance of detectors trained on augmented dataset outperforms those trained on original dataset.

关键词： Pedestrian detection augmentation dataset

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An Underwater Robotic system With a Soft Continuum Manipulator for Autonomous Aquatic Grasping

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2024年第2期29卷 1007-1018页

作者： Liu, Jiaqi Song, Zhuheng Lu, Yue Yang, Hui Chen, Xingyu Duo, Youning Chen, Bohan Kong, Shihan Shao, Zhuyin Gong, Zheyuan Wang, Shiqiang Ding, Xilun Yu, Junzhi Wen, Li Beihang Univ Sch Mech Engn & Automat Beijing 100191 Peoples R China Chinese Acad Sci Inst Deep Sea Sci & Engn Sanya 572000 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Guangdong Acad Sci Inst Semicond Guangzhou 510610 Guangdong Peoples R China Peking Univ Coll Engn Dept Adv Mfg & Robot Beijing 100871 Peoples R China Univ Toronto Toronto ON M5S 1A1 Canada Peking Univ Coll Engn State Key Lab Turbulence & Complex Syst Beijing 100871 Peoples R China

Delicate underwater manipulation tasks such as biological specimen collection are promising fields that require new robotic designs and intelligent robotic technologies. In this study, we proposed an automatic aquatic object-collecting system with a soft manipulator controlled by a reinforcement learning-based controller. For underwater sensing, we implemented a visual perception framework to restore the quality of the underwater image, detect the seafood animals, and track the target's position. The online learning ability of the reinforcement learning-based controller endowed strong adaptability for the soft manipulator against underwater disturbances. The water tank grasping tests show a 91.7% successful grasping rate without flow disturbance and 83.3% with flow disturbances. We demonstrated that the soft robotic collecting system gripped seafood animals in a lab aquarium as well as the natural seabed environment. The real-world experimental results showed that the robot successfully collected 28 shells within 40 min at a water depth of 15 m and even completed grasping tasks in a dark environment. Our results demonstrated that this manipulator prototype is potentially applicable for fully autonomous delicate objects underwater.

关键词： Grasping Robots Soft robotics Manipulator dynamics Task analysis Robot kinematics Biology Machine learning soft robotics underwater grasping

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A novel varying-parameter periodic rhythm neural network for solving time-varying matrix equation in finite energy noise environment and its application to robot arm

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NEURAL COMPUTING & APPLICATIONS 2023年第30期35卷 22577-22593页

作者： Li, Chunquan Zheng, Boyu Ou, Qingling Wang, Qianqian Yue, Chong Chen, Limin Zhang, Zhijun Yu, Junzhi Liu, Peter X. Nanchang Univ Sch Informat Engn Nanchang 330031 Peoples R China South China Univ Technol Sch Automat Sci & Engn Guangzhou 510640 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Peking Univ Coll Engn State Key Lab Turbulence & Complex Syst Dept Mech & Engn SciBIC ESAT Beijing 100871 Peoples R China Carleton Univ Dept Syst & Comp Engn Ottawa ON K1S 5B6 Canada

Solving matrix equation with noise interference is a challenging problem in mathematical and engineering applications. Unlike the traditional recurrent neural network, a novel varying-parameter periodic rhythm neural network (VP-PRNN) is proposed and used to solve the time-varying matrix equation in finite energy noise environment online. Particularly, VP-PRNN can enable the state solution to converge to the theoretical solution rapidly and robustly, which is also proved by theoretical analysis. Four kinds of noise are used to test the system, which proves the effectiveness of VP-PRNN. Compared with the zeroing neural network and circadian rhythms learning network with fixed parameters, VP-PRNN with variable parameters shows superior convergence performance in the disturbance of finite energy noise.

关键词： Zeroing neural network Varying-parameter Periodic rhythm Time-varying matrix equation Finite energy noise

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Parallel Treasury for TRUE DAOs: Model, Indicators and Mechanism

Parallel Treasury for TRUE DAOs: Model, Indicators and Mecha...

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Australian and New Zealand control Conference (ANZCC)

作者： Guan, Sangtian Li, Juanjuan Ding, Wenwen Wang, Fei-Yue Chinese Acad Sci State Key Lab Multimodal Artificial Intelligence Inst Automat Beijing 100190 Peoples R China Macau Univ Sci & Technol Fac Innovat Engn Macau 999078 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Fac Innovat Engn Macau 999078 Peoples R China

ISBN: (纸本)9798350314977

In response to concerns over the centralization tendency in the decentralized autonomous organizations (DAOs), TRUE autonomous organizations and operations (TAOs or TRUE DAOs) have been proposed recently. TAOs aim at spreading equitable value distribution and democratized decision-making, distinguishing them from their DAOs counterparts. This study focuses on the treasury within TAOs, which acts as a central fund pool and a crucial element in the decentralized economy (DeEco) system. First, against a backdrop of potential black swan events and other long-tail unforeseen challenges, a reference model for the intelligent treasury management of TAOs is proposed. Then, an evaluation system, namely VALID, is presented with metrics including verifiability, anti-volatility, legitimacy, inclusiveness, and decentralization. Furthermore, a novel parallel treasury management mechanism is proposed to demonstrate a virtual-real interactive closed-loop management and control paradigm of the treasury, thereby fostering the formulation and development of DeEco. This research provides a comprehensive perspective on intelligent treasury management of TAOs and their role in sustainable advancement of DeEco.

关键词： Decision making

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A novel scheduling strategy for virtual power plant based on power market dynamic triggers

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APPLIED ENERGY 2023年第1期350卷

作者： Wang, Yanjia Xu, Chao Xie, Da Gu, Chenghong Zhao, Pengfei Gong, Jinxia Pan, Mingjie Wang, Xitian Shanghai Jiao Tong Univ Dept Elect Engn Shanghai Peoples R China Univ Bath Dept Elect & Elect Engn Bath England Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Shanghai Univ Elect Power Dept Elect Power Engn Shanghai Peoples R China

For the scheduling problem of virtual power plants (VPPs), this paper aims to propose a dynamic trigger scheduling strategy that integrates objective grid information and subjective judgment factors affecting VPP scheduling. The strategy design involves setting initial incentive electricity prices and optimizing price adjustment efficiency. Firstly, this paper establishes a reference incentive electricity price model to derive the initial reference electricity price for the dispatching process. Then, a response willingness model is proposed to establish the relationship between electricity price and VPP response, improving the accuracy of the initial reference electricity price and reducing the frequency of subsequent price adjustments in the actual trigger. Finally, this paper utilizes the groundbreaking dynamic trigger method to adjust the price based on the actual VPP response, obtaining the optimal VPP incentive electricity price. We use Matlab to verify this strategy, and the experimental results show that the average response error using this strategy is reduced by 3.33 kW compared to the contrastive literature. Moreover, scheduling task non-completion does not occur in this method. Thus, the accuracy and reliability of the method are verified.

关键词： VPP scheduling Dynamic trigger Incentive electricity price Response willingness

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MetaSocieties in Metaverse: MetaEconomics and Metamanagement for MetaEnterprises and MetaCities

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systemS 2022年第1期9卷 2-7页

作者： Wang, Fei-Yue Qin, Rui Wang, Xiao Hu, Bin Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China Lanzhou Univ Sch Informat Sci & Engn Gansu Prov Key Lab Wearable Comp Lanzhou 730000 Gansu Peoples R China

Welcome to the first issue of the IEEE Transactions on Computational Social systems (TCSS) of 2022. We would like to take this opportunity to express our sincere thanks to our associate editors, reviewers, authors, and readers for your great support and effort devoted to IEEE TCSS. Happy New Year to you all, and cheers to health, happiness, and high-producing in 2022!

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Metaverses-Based Parallel Oil Fields in CPSS: A Framework and Methodology

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IEEE TRANSACTIONS ON systemS MAN CYBERNETICS-systemS 2023年第4期53卷 2138-2147页

作者： Wang, Xingxia Cheng, Xiang Lu, Jingwei Kwan, Oliver Li, Shixing Ping, Zhixing Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automation State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China Motion G Inc Singapore City 068898 Singapore North Automatic Control Technol Inst Taiyuan 030006 Peoples R China

Aiming to provide a novel paradigm of oil fields, metaverses-based parallel oil fields are proposed in this article. Compared with the existing smart/intelligent oil fields in cyber-physical systems (CPS), parallel oil fields can take human factors into full consideration and expand the operation space to cyber-physical-social systems (CPSS), which can be regarded as the abstract and scientific explanation of metaverses. In the proposed parallel oil fields, there are three kinds of workers (human workers, digital workers, and robotic workers) coordinating to construct a more reliable and intelligent oil field. Furthermore, the framework and methodology of parallel oil fields are illustrated by parallel systems and the artificial systems, computational experiments, and parallel executions (ACP) approach. Based on the proposed framework, parallel oil fields are capable of generating a more trustworthy artificial system and guaranteeing the realization of the 6S (safety, security, sustainability, sensitivity, service, and smartness) goal. Finally, based on dynamometer cards, fault diagnosis of sucker rod pumping systems (SRPS) is investigated in parallel oil fields.

关键词： Artificial systems computational experiments and parallel executions (ACP) approach Cyber-physical-social systems (CPSS) digital workers fault diagnosis metaverses-based parallel oil fields parallel systems

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