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arXiv 2024年

作者： Wu, Xiaoyi Chen, Yushuai Li, Zhan Hong, Ziyang Hu, Liang The Department of Automation School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150001 China

Odometry is a crucial component for successfully implementing autonomous navigation, relying on sensors such as cameras, LiDARs and IMUs. However, these sensors may encounter challenges in extreme weather conditions, such as snowfall and fog. The emergence of FMCW radar technology offers the potential for robust perception in adverse conditions. As the latest generation of FWCW radars, the 4D mmWave radar provides point cloud with range, azimuth, elevation, and Doppler velocity information, despite inherent sparsity and noises in the point cloud. In this paper, we propose EFEAR-4D, an accurate, highly efficient, and learning-free method for large-scale 4D radar odometry estimation. EFEAR-4D exploits Doppler velocity information delicately for robust ego-velocity estimation, resulting in a highly accurate prior guess. EFEAR-4D maintains robustness against point-cloud sparsity and noises across diverse environments through dynamic object removal and effective region-wise feature extraction. Extensive experiments on two publicly available 4D radar datasets demonstrate state-of-the-art reliability and localization accuracy of EFEAR-4D under various conditions. Furthermore, we have collected a dataset following the same route but varying installation heights of the 4D radar, emphasizing the significant impact of radar height on point cloud quality - a crucial consideration for real-world deployments. Our algorithm and dataset will be available soon at https://***/CLASS-Lab/EFEAR-4D. © 2024, CC BY-NC-SA.

关键词： Millimeter waves

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State controller with Improved Response Speed for Linear Discrete SISO Systems

State Controller with Improved Response Speed for Linear Dis...

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2022 International Conference Automatics and Informatics, ICAI 2022

作者： Nikolov, Nikola Alexandrova, Mariela Gaziyeva, Rano Ubaydullayeva, Shakhnoza Technical University of Varna Faculty of Computer Sciences and Automation Department of Automation Varna9010 Bulgaria National Research University Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Department Automation and Control of Technology Process in Production Tashkent100000 Uzbekistan

ISBN: (数字)9781665476256

ISBN: (纸本)9781665476256

This paper presents an opportunity to create a linear discrete system (LDS) with a modal state controller for Single Input Single Output objects control. The created controller has an integrating element and a relationship between the set point (SP) and the control object (CO), implemented with an inverse model on the object. The proposed system guarantees handling of the perturbances and providing an improvement in the system performance as in PID-controller systems. In structure proposed, an LQR state controller could be used instead of the MSC. © 2022 IEEE.

关键词： Three term control systems

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A Recurrent Neural Network Based Bicriteria Repetitive Motion Collision Avoidance Scheme for Motion Planning of Dual Redundant Manipulators 13

A Recurrent Neural Network Based Bicriteria Repetitive Motio...

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13th International Conference on Intelligent control and Information Processing, ICICIP 2025

作者： Chen, Shirui Gao, Huanli Hu, Shaolin Zhang, Zhijun The School of Automation Science and Engineering South China University of Technology Guangzhou510640 China The School of Automation Guangdong University of Petrochemical Technology Maoming Guangzhou525000 China The Guangzhou Key Laboratory of Brain-Computer Interaction and Applications Guangzhou China The Key Library of Autonomous Systems and Network Control Ministry of Education The School of Automation Science and Engineering South China University of Technology Guangzhou510640 China Guangzhou510555 China The Jiangxi Thousand Talents Plan Nanchang University Nanchang330031 China The College of Computer Science and Engineering Jishou University Jishou416000 China Guangzhou510335 China The Shaanxi Provincial Key Laboratory of Industrial Automation School of Mechanical Engineering Shaanxi University of Technology Hanzhong723001 China The School of Information Science and Engineering Changsha Normal University Changsha410100 China The School of Automation Science and Engineering Maoming525000 China The Institute of Artificial Intelligence and Automation Guangdong University of Petrochemical Technology Maoming525000 China

ISBN: (纸本)9798331516147

To achieve low joint-angle drift and avoid mutual collision between dual redundant manipulators (DRMs) when they are doing collaboration works, a recurrent neural network based bicriteria repetitive motion collision avoidance (BRMCA) scheme is proposed for motion planning of DRMs. By designing a combined optimization objective encompassing both repetitive motion criterion and collision avoidance criterion, the BRMCA scheme has larger feasible region and less constraint contradiction issues compared with traditional inequality constraints based method. Furthermore, by incorporating velocity-level kinematic model and physical limits of DRMs into the scheme, a time varying quadratic programming (TVQP) problem is formulated. The linear variational inequality-based primal–dual neural network (LVI-PDNN) is used to solve the proposed scheme due to the high accuracy and low computation complexity. Finally, through comparison simulations of tracking Circle-shape and C-shape trajectories between BRMCA scheme and minimum velocity norm (MVN) scheme, it exhibits that the proposed BRMCA scheme can achieve low joint-angle drift, collision avoidance and high tracking accuracy when DRMs are doing cooperative tasks. © 2025 IEEE.

关键词： Recurrent neural networks

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Indirect adaptive observer control (I-AOC) design for truck–trailer model based on T–S fuzzy system with unknown nonlinear function

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Complex and Intelligent Systems 2024年第5期10卷 7311-7331页

作者： Aslam, Muhammad Shamrooz Bilal, Hazrat Chang, Wer-Jer Yahya, Abid Badruddin, Irfan Anjum Kamangar, Sarfaraz Hussien, Mohamed Artificial Intelligence Research Institute China University of Mining and Technology Department of Automation University of Science and Technology of China Department of Marine Engineering of National Taiwan Ocean University (NTOU) Department of Electrical Computer and Telecommunications Engineering Botswana International University of Science and Technology Department of Mechanical Engineering College of Engineering King Khalid University Department of Chemistry Faculty of Science King Khalid University

Tracking is a crucial problem for nonlinear systems as it ensures stability and enables the system to accurately follow a desired reference signal. Using Takagi–Sugeno (T–S) fuzzy models, this paper addresses the problem of fuzzy observer and control design for a class of nonlinear systems. The Takagi–Sugeno (T–S) fuzzy models can represent nonlinear systems because it is a universal approximation. Firstly, the T–S fuzzy modeling is applied to get the dynamics of an observational system in order to estimate the unmeasurable states of an unknown nonlinear system. There are various kinds of nonlinear systems that can be modeled using T–S fuzzy systems by combining the input state variables linearly. Secondly, the T–S fuzzy systems can handle unknown states as well as parameters known to the indirect adaptive fuzzy observer. A simple feedback method is used to implement the proposed controller. As a result, the feedback linearization method allows for solving the singularity problem without using any additional algorithms. A fuzzy model representation of the observation system comprises parameters and a feedback gain. The Lyapunov function and Lipschitz conditions are used in constructing the adaptive law. This method is then illustrated by an illustrative example to prove its effectiveness with different kinds of nonlinear functions. A well-designed controller is effective and its performance index minimizes network utilization—this factor is particularly significant when applied to wireless communication systems. © The Author(s) 2024.

关键词： Adaptive observer control Feedback control design Indirect method Lyapunov–Krasovskii candidate T–S fuzzy models

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Simultaneous Estimation of Human Motion Intention and Time-Varying Arm Stiffness for Enhanced Human-Robot Interaction

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IEEE Transactions on Cognitive and Developmental Systems 2024年第3期17卷 510-524页

作者： Wu, Huayang Zhu, Chengzhi Cheng, Long Yang, Chenguang Li, Yanan University of Sussex Department of Engineering and Design BrightonBN1 9RH United Kingdom South China University of Technology Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering Guangzhou510640 China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China University of Liverpool Department of Computer Science LiverpoolL69 3BX United Kingdom

Recent advances in physiological human motor control research indicate that human endpoint stiffness magnitude increases linearly with grasp force. Based on these findings, a scheme was proposed in this paper to integrate the linear quadratic estimation (LQE) filter with the stiffness model inferred from grasp force, which can simultaneously estimate the human arm's stiffness and motion intention. Then, an online variable impedance controller (VIC) was designed based on previous estimations for physical human-robot interaction (pHRI). The proposed stiffness model and estimation method were validated through experiments using a planar robotic interface. In order to assess its performance in practical pHRI tasks, the implementation of human arm stiffness and intention estimation combining with VIC was extended to a teleoperation peg-in-hole and robot-assisted rehabilitation tasks. The experimental results demonstrate that the proposed method can effectively estimate human motion intention and arm stiffness simultaneously. Compared to existing methods, the proposed VIC enhances pHRI in terms of increased flexibility, effective guidance, and reduced human effort. © 2016 IEEE.

关键词： Human robot interaction

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Flexible Manufacturing Concept at Bosch: A low-cost implementation of an Industry 4.0 concept 19

Flexible Manufacturing Concept at Bosch: A low-cost implemen...

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19th IMEKO TC10 Conference on MACRO meets NANO in Measurement for Diagnostics, Optimization and control

作者： Fükő, László Szaller, Ádám Colangelo, Eduardo Nick, Gábor Kádár, Botond Bosch Power Tool Ltd. Miskolc3526 Hungary Institute for Computer Science and Control Budapest1111 Hungary Fraunhofer Institute for Manufacturing Engineering and Automation IPA Stuttgart70569 Germany EPIC InnoLabs Nonprofit Ltd. Budapest1111 Hungary

ISBN: (纸本)9781713884125

Nowadays production companies are in a difficult situation since batch sizes are decreasing, the number of product variants is growing, and the demand is difficult to forecast. New technologies enable to design more complex production systems capable of handling these challenges, but these "Industry 4.0 solutions" are often very expensive and hard to implement. In Bosch Power Tool Ltd. (Hungary), a flexible manufacturing concept was implemented, which enables to produce efficiently even with batch size one, requires much less space from the shop floor, prevents disruptions in production, and last but not least realized in from a relatively small budget. The concept introduced in this paper can be used as a best practice for manufacturing companies facing similar challenges. © 2023 19th IMEKO TC10 Conference "MACRO meets NANO in Measurement for Diagnostics, Optimization and control".

关键词： flexible manufacturing Industry 4.0 smart manufacturing

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Video2Reward: Generating Reward Function from Videos for Legged Robot Behavior Learning 27

Video2Reward: Generating Reward Function from Videos for Leg...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Zeng, Runhao Zhou, Dingjie Liang, Qiwei Liu, Junlin Li, Hui Huang, Changxin Li, Jianqiang Hu, Xiping Sun, Fuchun Artificial Intelligence Research Institute Shenzhen MSU-BIT University China College of Mechatronics and Control Engineering Shenzhen University China College of Computer Science and Software Engineering Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Department of Computer Science and Technology Tsinghua University China

ISBN: (纸本)9781643685489

Learning behavior in legged robots presents a significant challenge due to its inherent instability and complex constraints. Recent research has proposed the use of a large language model (LLM) to generate reward functions in reinforcement learning, thereby replacing the need for manually designed rewards by experts. However, this approach, which relies on textual descriptions to define learning objectives, fails to achieve controllable and precise behavior learning with clear directionality. In this paper, we introduce a new video2reward method, which directly generates reward functions from videos depicting the behaviors to be mimicked and learned. Specifically, we first process videos containing the target behaviors, converting the motion information of individuals in the videos into keypoint trajectories represented as coordinates through a video2text transforming module. These trajectories are then fed into an LLM to generate the reward function, which in turn is used to train the policy. To enhance the quality of the reward function, we develop a video-assisted iterative reward refinement scheme that visually assesses the learned behaviors and provides textual feedback to the LLM. This feedback guides the LLM to continually refine the reward function, ultimately facilitating more efficient behavior learning. Experimental results on tasks involving bipedal and quadrupedal robot motion control demonstrate that our method surpasses the performance of state-of-the-art LLM-based reward generation methods by over 37.6% in terms of human normalized score. More importantly, by switching video inputs, we find our method can rapidly learn diverse motion behaviors such as walking and running. © 2024 The Authors.

关键词： Robots

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Modeling and Operating Point Analysis for Aquatic Translational Motion of a Cross-Medium Vehicle 42

Modeling and Operating Point Analysis for Aquatic Translatio...

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42nd Chinese control Conference, CCC 2023

作者： Dou, Minghao Liu, Xuchen Huang, Dongyue Wang, Biao Cui, Jinqiang Ren, Qinyuan Dou, Lihua Chen, Jie Chen, Ben M. Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Shatin N.T. Hong Kong College of Automation Engineering Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing China Peng Cheng Laboratory Guangdong Shenzhen China College of Control Science and Engineering Zhejiang University Zhejiang Hangzhou China Automation Beijing Institute of Technology Beijing China

ISBN: (纸本)9789887581543

Modeling of cross-medium vehicles with complex shapes still requires a thorough investigation. This paper proposes a multi-method combination modeling approach to tackle such a problem. First-principle model is derived to determinate a model structure. Experiments are then set up to estimate parameters related to its rigid-body model and propulsion system. Computational fluid dynamics (CFD) is performed to calculate and identify coefficients related to surrounding fluid. Base on the model obtained, we systematically investigate the possible steady motion of the cross-medium vehicle and analyze their related performance. Results are instrumental for designing controllers for the vehicle to perform autonoumous missions. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Computational fluid dynamics

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A Robust Path Planning of Messenger UAV for Air-Ground Coordination Under Road Network Constraints

A Robust Path Planning of Messenger UAV for Air-Ground Coord...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Wang, Yuyang Xin, Bin Ding, Yulong Yin, Zhen He, Bin School of Automation Beijing Institute of Technology Beijing100081 China Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing100081 China Tongji University Department of Control Science and Engineering Shanghai China

ISBN: (纸本)9781665481090

This paper addresses the path planning problem for unmanned aerial vehicle (UAV), where a UAV serves as a messenger to periodically traverse over road-constrained ground vehicles (GVs) to relay information. The GVs may not move on the road network with the velocities agreed with the UAV due to their movement uncertainties. The UAV path planning problem can be formulated as the Dynamic Dubins Traveling Salesman Problem with Uncertain Neighborhood (DDTSPUN). To address the uncertainty in GVs motion, we define robust neighborhoods and corridors and prove that the UAV visiting these areas can revisit GVs reliably, thus transforming DDTSPUN into a Revisit-time-constrained Dubins Traveling Salesman Problem with Neighborhood (RDTSPN). To address the RDTSPN, we propose an online heuristic path planning algorithm. This algorithm incorporates a gradient-based method for visiting robust neighborhoods and a sampling-based search strategy along robust corridors to obtain the Dubins paths of UAV that achieve the robust visit for each GV. Finally, computational experiments demonstrate its advantage over other benchmark algorithms in obtaining the shortest path satisfying UAV curvature constraints, and ensuring robust access to all GVs. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Distributed Optimization with Finite Bit Adaptive Quantization for Efficient Communication and Precision Enhancement 63

Distributed Optimization with Finite Bit Adaptive Quantizati...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. Artificial Intelligence Thrust of the Information Hub Guangzhou China The Hong Kong University of Science and Technology Department of Computer Science and Engineering Clear Water Bay Hong Kong Aalto University School of Electrical Engineering Department of Electrical Engineering and Automation Espoo Finland University of Cyprus School of Engineering Department of Electrical and Computer Engineering Nicosia1678 Cyprus Kth Royal Institute of Technology Division of Decision and Control Systems StockholmSE-100 44 Sweden

ISBN: (纸本)9798350316339

In realistic distributed optimization scenarios, individual nodes possess only partial information and communicate over bandwidth constrained channels. For this reason, the development of efficient distributed algorithms is essential. In our paper we addresses the challenge of unconstrained distributed optimization. In our scenario each node's local function exhibits strong convexity with Lipschitz continuous gradients. The exchange of information between nodes occurs through 3-bit bandwidth-limited channels (i.e., nodes exchange messages represented by a only 3 -bits). Our proposed algorithm respects the network's bandwidth constraints by leveraging zoom-in and zoom-out operations to adjust quantizer parameters dynamically. We show that during our algorithm's operation nodes are able to converge to the exact optimal solution. Furthermore, we show that our algorithm achieves a linear convergence rate to the optimal solution. We conclude the paper with simulations that highlight our algorithm's unique characteristics. © 2024 IEEE.

关键词： Bandwidth

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