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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2023年第2期8卷 1607-1623页

作者： Liang, Shuang Cao, Zhiqiang Wang, Chengpeng 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 Dept Adv Mfg & Robot State Key Lab Turbulence & Complex SystBIC ESAT Beijing 100871 Peoples R China

LiDAR odometry (LO) has gained popularity in recent years due to accurate depth measurement and robustness to illumination. Typically, the solutions based on scan-to-map matching mainly optimize current pose. To further reduce the accumulated error of pose estimation, the fixed-lag smoothing that optimizes fixed-size poses simultaneously by matching corresponding point features of multiple frames becomes necessary. The integration of fixed-lag smoothing with LO still needs further exploration. In this paper, a general fixed-lag smoothing module is proposed, which can be appended to existing LO framework to improve the consistency of trajectory. Also, a fast scan-to-map matching module based on sparse features is developed to guarantee the real-time performance. Besides, the feature-centric feature management strategy is adopted in both scan-to-map matching and fixed-lag smoothing modules, which makes the proposed LO efficient. On this basis, a hierarchical estimation-based LiDAR odometry is presented, where low-level scan-to-map matching estimates pose of each frame by aligning associated features in the frame and corresponding surrounding map with high efficiency, and high-level fixed-lag smoothing further optimizes keyframe poses in a sliding window by matching associated features among multiple frames with high accuracy. As a result, a fast and accurate pose estimation is achieved, which is verified by experiments on the KITTI dataset, Newer College dataset, and an actual outdoor scenario.

关键词： Feature extraction Laser radar Smoothing methods Pose estimation Point cloud compression Real-time systems Three-dimensional displays LiDAR odometry hierarchical estimation scan-to-map matching fixed-lag smoothing

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Distributed Formation control for a Multirobotic Fish system With Model-Based Event-Triggered Communication Mechanism

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2023年第11期70卷 11433-11442页

作者： Dai, Shijie Wu, Zhengxing Zhang, Pengfei Tan, Min Yu, Junzhi Univ Chinese Acad Sci Sch Artificial IntellIigence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Peking Univ Dept Adv Mfg & Robot Coll Engn State Key Lab Turbulence & Complex SystBIC ESAT Beijing 100871 Peoples R China

This article confronts the formation control problem for a multirobotic fish system with event-triggered communication mechanism. A 3-D distributed formation control framework is proposed to drive the robotic fish agents to an anticipated configuration aligning with a moving target. In particular, a consensus-based formation control law is intended to realize the two-stage formation control process. Taking the energy-constrained occasions into consideration, the communication structure and event-triggered protocols are initially tailored. Meanwhile, the Lyapunov function is employed and the globally asymptotic stability of the proposed method is fully demonstrated. Afterwards, making use of the local measurements of triggering times, the unscented Kalman filter is introduced and a novel model-based event-triggered mechanism is put forward to further mitigate otiose communication consumption. Finally, adequate simulations and experiments are carried out to verify the effectiveness and robustness of the proposed scheme. Thereby, the proposed formation control frame offers great potential for future practical marine operations of the underwater multiagent systems.

关键词： Formation control model-based eventtriggered mechanism (ETM) robotic fish underwater multiagent system

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Barrier-Based Adaptive Line-of-Sight 3-D Path-Following system for a Multijoint Robotic Fish With Sideslip Compensation

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IEEE TRANSACTIONS ON CYBERNETICS 2023年第7期53卷 4204-4217页

作者： Dai, Shijie Wu, Zhengxing Wang, Jian Tan, Min Yu, Junzhi 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 Peking Univ Coll Engn Dept Adv Mfg & Robot BIC ESATState Key Lab Turbulence & Complex Syst Beijing 100871 Peoples R China

This article proposes a novel barrier-based adaptive line-of-sight (ALOS) three-dimensional (3-D) path-following system for an underactuated multijoint robotic fish. The framework of the developed path-following system is established based on a detailed dynamic model, including a barrier-based ALOS guidance strategy, three integrated inner-loop controllers, and a nonlinear disturbance observer (NDOB)-based sideslip angle compensation, which is employed to preserve a reliable tracking under a frequently varying sideslip angle of the robotic fish. First, a barrier-based convergence strategy is proposed to deal with probable along-track error disruption and suppress the error within a manageable range. Meanwhile, an improved adaptive guidance scheme is adopted with an appropriate look-ahead distance. Afterward, a novel NDOB-based sideslip angle compensation is put forward to identify the varying sideslip angle independent of speed estimation. Subsequently, inner-loop controllers are intended for regulation about the controlled references, including a super-twisting sliding-mode control (STSMC)-based speed controller, a global fast terminal sliding-mode control (GFTSMC)-based heading controller, and a GFTSMC-based depth controller. Finally, simulations and experiments with quantitative comparison in 3-D linear and helical path following are presented to verify the effectiveness and robustness of the proposed system. This path-following system provides a solid foundation for future marine autonomous cruising of the underwater multijoint robot.

关键词： Robots Robot kinematics Adaptive systems Navigation Solid modeling Force complex systems 3-D path-following adaptive line-of-sight (LOS) guidance and control robotic fish time-varying sideslip angle

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High Precision Calibration for Three-Dimensional Vision-Guided Robot system

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2023年第1期70卷 624-634页

作者： Liu, Zhicheng Liu, Xilong Cao, Zhiqiang Gong, Xurong Tan, Min 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 BIC ESAT Coll Engn Dept Adv Mfg & Robot State Key Lab Turbulence & Complex Syst Beijing 100871 Peoples R China

Calibration is an important premise for vision-guided robot system, especially for precise industrial operations on curved surfaces. Most of existing methods focus on one or partial union of errors including assembly error of the robot, relative pose error between the vision unit and the robot, or installation error of end effector, which is still challenging in practice. To solve this problem, this article proposes a new calibration method based on error correction matrix by which different manifestations of each error is unified. As the nonlinear equations formed by these matrices cannot be solved analytically, a numerical optimization solution based on Lie algebra is presented. Specifically, the matrices acquisition is formulated as the problem of minimizing the sum of distance deviations between actual and ideal tool center points. This problem is then solved by differentiating these matrices with a form of left multiplicative perturbation. In this way, a high precision joint calibration with multisource errors is achieved. The proposed method is verified by simulations and experiments.

关键词： Robots Calibration Robot kinematics Mathematical models End effectors Cameras Robot vision systems Calibration error correction matrix unified model vision-guided robot

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Macau's New ITSS Chapter: An Experiment With New Artificial Intelligence and Decentralized Autonomous Science for Future Mobility

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IEEE INTELLIGENT TRANSPORTATION systemS MAGAZINE 2025年第2期17卷 138-140页

作者： Wang, Fei Yue Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Macau Inst Syst Engn Taipa Macau Peoples R China

Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.

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Development of a Penguin-Inspired Swimming Robot With Air Lubrication system

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2023年第3期70卷 2780-2789页

作者： Pan, Jie Zhou, Ziye Wang, Jian Zhang, Pengfei Yu, Junzhi Peking Univ Dept Adv Mfg & Robot State Key Lab Turbulence & Complex Syst Coll EngnBIC ESAT Beijing 100871 Peoples R China 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

In this article, a novel robotic penguin equipped with air lubrication system is developed. Through mimicking the agile movements of biological penguins, two degrees of freedom (DOF) wings including heaving and pitching motions, and a buoyancy-driven system for ascending and diving are particularly designed. Meanwhile, a complete 3-D dynamic model is established based on the Morrison equation, and the hydrodynamic parameters are determined with experimental results. Then, taking the bioinspired central pattern generators as the main actuation, the 3-D locomotion performance is discussed. More importantly, inspired by the leaping behavior of penguins, a unique air lubrication system is developed, and the obtained results verify the effectiveness of the mechatronic design. This work will offer valuable insight into the future development and control of next-generation versatile underwater vehicles capitalizing on the air lubrication mechanism.

关键词： 3-D dynamic modeling air lubrication system motion control robotic penguin

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The Future of management: DAO to Smart Organizations and Intelligent Operations

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IEEE TRANSACTIONS ON systemS MAN CYBERNETICS-systemS 2023年第6期53卷 3389-3399页

作者： Li, Juanjuan Qin, Rui Wang, Fei-Yue Chinese Acad Sci Inst Automation State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Macau Inst Syst Engn Taipa Macao Peoples R China

In the future, management in smart societies will revolve around knowledge workers and the works they produce. This article is committed to explore new management framework, model, paradigm, and solution for organizing, managing, and measuring knowledge works. First, the parallel management framework is presented that would allow for the virtual-real interactions of humans in social space, robots in physical space, and digital humans in cyberspace to realize descriptive, predictive, and prescriptive intelligence for management. Then, the management foundation models are proposed by fusing scenarios engineering with artificial intelligence foundation models and cyber-physical-social systems. Moreover, the new management paradigm driven by decentralized autonomous organizations and operations is formulated for the advancement of smart organizations and intelligent operations. On these basis, the management operating systems that highlight features of simple intelligence, provable security, flexible scalability, and ecological harmony are finally put forward as new management solution.

关键词： Decentralized autonomous organizations and operations (DAO) management foundation model management intelligence management operating system (MOS) metaverse parallel management

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Autonomous Dynamic Hitch-Hiking control of a Bionic Robotic Remora

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2024年第3期71卷 2893-2902页

作者： Zhang, Pengfei Wu, Zhengxing Chen, Di Tan, Min 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 Dept Adv Mfg & Robot Coll Engn State Key Lab Turbulence & Complex Syst Beijing 100871 Peoples R China Guangdong Ocean Univ Coll Elect & Informat Engn Zhanjiang 524088 Peoples R China

Remora suckerfish and its hitch-hiking behavior bring enormous inspiration into the engineering field. In this article, a bioinspired hitch-hiking behavior is accomplished automatically by a robotic remora, which creates possibilities for prolonging its endurance and multirobot cooperation. First, the definition of the hitch-hiking task and the mechatronic design of robotic remora are introduced. Then, aiming at the hitch-hiking task, the LED-marker-based underwater visual localization method and planar state synchronization controller are developed. The localization method includes a complete framework from LED detection to marker pose optimization, which considers the refraction correction to improve the localization precision in water. The synchronization controller is decomposed into the lateral and longitudinal subcontrollers to overcome the challenges caused by underactuated dynamic. Besides, a finite state machine is designed to model the state and action transition during the hitch-hiking task. Extensive experimental results demonstrate the effectiveness of the proposed method. The autonomous hitch-hiking task toward a moving host is successfully implemented by a robotic fish for the first time. Such results may offer valuable insights into the future autonomous operation of underwater robots.

关键词： Autonomous control bioinspired adhesion robotic fish underwater visual localization

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Separate control Strategy for a Biomimetic Gliding Robotic Fish

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2022年第5期27卷 2535-2544页

作者： Dong, Huijie Wu, Zhengxing Zhang, Pengfei Wang, Jian Tan, Min 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 Dept Adv Mfg & Robot Coll Engn State Key Lab Turbulence & Complex SystBIC ESAT Beijing 100871 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

In this article, we present a novel separate strategy to control the pitch attitude and the gliding direction for a biomimetic gliding robotic fish by the coordination of the external and internal control surfaces. First, we derive the gliding dynamics and hydrodynamics within the framework of the extended angle of attack (AOA), based on which the gliding model is decomposed into pitch and velocity terms. Next, the backstepping and model predictive controllers are designed to regulate pitch angle using a movable mass and an AOA using pectoral fins based on their control features, respectively. Further, extensive simulations encompassing separate control and path following with desired pitch attitude are conducted to verify the feasibility and superiority of the proposed control strategy. More importantly, to capture the real-time gliding states in practical environment, we develop a gliding measurement and control system. Through the system, the aquatic experiments are carried out to further verify the effectiveness of the proposed separate control strategy. The obtained results offer valuable insight into the development of complex motion control of the gliding robots, laying a solid foundation for diversified underwater missions besides visual perception and autonomous docking.

关键词： Biomimetic robot gliding robotic fish motion control pitch control underwater robotics

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Robust Multitask Learning With Sample Gradient Similarity

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IEEE TRANSACTIONS ON systemS MAN CYBERNETICS-systemS 2024年第1期54卷 497-506页

作者： Peng, Xinyu Chang, Cheng Wang, Fei-Yue Li, Li Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100080 Peoples R China Tsinghua Univ Dept Automat Tsinghua Natl Lab Informat Sci & Technol Beijing 100084 Peoples R China

Multitask learning has led to great success in many deep learning applications during the last decade. However, recent experiments have demonstrated that the performance of multitask learning depends on how to balance the relationship between different tasks. Therefore, many approaches have been proposed to adjust per-task gradient directions or design a more appropriate task reweighting scheme based on task-level statistics. In this article, we discuss how to boost the performance of multitask learning by using more fine-grained sample gradient information. To this end, we propose the concept of sample gradient similarity, which measures the agreement between the sample gradient for a task and the true gradient. Based on this concept, greater weight is assigned to more consistent tasks and more robust training samples to improve the training process of multitask learning. Extensive experimental results show that our proposed method outperforms the state-of-the-art algorithms on a series of challenging multitask datasets.

关键词： Deep learning Automation multitask learning sample gradient sample reweighting task reweighting

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