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arXiv 2024年

作者： Wang, Xiaorui Sha, Zeyu Zhang, Feitian The Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China The Department of Advanced Manufacturing and Robotics The State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University Beijing100871 China

Underwater robots play a crucial role in exploring aquatic environments. The ability to flexibly adjust their attitudes is essential for underwater robots to effectively accomplish tasks in confined space. However, the highly coupled six degrees of freedom dynamics resulting from attitude changes and the complex turbulence within limited spatial areas present significant challenges. To address the problem of attitude control of underwater robots, this letter investigates large-range pitch angle tracking during station holding as well as simultaneous roll and yaw angle control to enable versatile attitude adjustments. Based on dynamic modeling, this letter proposes an adaptive integral sliding mode controller (AISMC) that integrates an integral module into traditional sliding mode control (SMC) and adaptively adjusts the switching gain for improved tracking accuracy, reduced chattering, and enhanced robustness. The stability of the closed-loop control system is established through Lyapunov analysis. Extensive experiments and comparison studies are conducted using a commercial remotely operated vehicle (ROV), the results of which demonstrate that AISMC achieves satisfactory performance in attitude tracking control in confined space with unknown disturbances, significantly outperforming both PID and SMC. Copyright © 2024, The Authors. All rights reserved.

关键词： Sliding mode control

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A Multi-Modal Approach Based on Large Vision Model for Close-Range Underwater Target Localization

arXiv

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arXiv 2024年

作者： Yang, Mingyang Sha, Zeyu Zhang, Feitian The Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China The Department of Advanced Manufacturing and Robotics The State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University Beijing100871 China

Underwater target localization uses real-time sensory measurements to estimate the position of underwater objects of interest, providing critical feedback information for underwater robots in tasks such as obstacle avoidance, scientific exploration, and environmental monitoring. While acoustic sensing is the most acknowledged and commonly used method in underwater robots and possibly the only effective approach for long-range underwater target localization, such a sensing modality generally suffers from low resolution, high cost and high energy consumption, thus leading to a mediocre performance when applied to close-range underwater target localization. On the other hand, optical sensing has attracted increasing attention in the underwater robotics community for its advantages of high resolution and low cost, holding a great potential particularly in close-range underwater target localization. However, most existing studies in underwater optical sensing are restricted to specific types of targets, thus lacking generalization capabilities. In addition, these studies typically focus on the design of estimation algorithms and ignore the influence of illumination conditions on the sensing performance, thus hindering wider applications in the real world. To address the aforementioned issues, this paper proposes a novel target localization method that assimilates both optical and acoustic sensory measurements to estimate the 3D positions of close-range underwater targets. The proposed sensing method integrates a large vision model with unique acoustic-based model prompt design to process multi-modal sensor measurements, ensuring the generalizability and robustness of underwater target localization. A test platform with controllable illumination conditions is developed. Extensive experiments are conducted, the results of which validate the effectiveness of the proposed method. Copyright © 2024, The Authors. All rights reserved.

关键词： Strain measurement

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High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System

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Journal of Bionic engineering 2022年第2期19卷 299-313页

作者： Yinlong Zhang Wei Liang Sichao Zhang Xudong Yuan Xiaofang Xia Jindong Tan Zhibo Pang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China The School of Computer Science and Technology Xidian UniversityXi’an 710071China Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeKonxville 37996USA Department of Automation Technology ABB Corporate Research Sweden72178 VästerasSweden

Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement Unit(IMU)to perceive ego motion and surrounding unstructured *** robot perception,a reliable and high-precision calibration between camera,IMU and manipulator is a critical *** paper introduces a novel calibration ***,we seek to correlate the spatial relationship between the sensing units and manipulator in a joint ***,the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent *** calibration has been evaluated on our collected visual inertial-manipulator *** systematic comparisons and analysis indicate the consistency,precision and effectiveness of our proposed calibration method.

关键词： Bio-inspired robotic system Monocular camera IMU Manipulator Calibration

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Design of a SMA actuated freeplay elimination device for stiffness enhancement of a folding fin

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Mechanical systems and Signal Processing 2025年 234卷

作者： Zhang, Rongru Chen, Gang Yue, Honghao Si, Mingyu State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150001 China Beijing Institute of Electronic System Engineering Beijing100854 China

The folding fin, essential for controlling aircraft flight attitude and maintaining stability, is extensively employed in aerospace vehicles. Inevitable freeplay within the structure, due to design, installation, and mechanical wear, reduce the stiffness of the folding fins and impair the aircraft's aerodynamic performance. Therefore, eliminating the freeplay in the folding fin is crucial for enhancing the aircraft's flight accuracy and stability. This paper introduces a novel freeplay elimination device utilizing SMA columns, which neither increases mass nor alters the aircraft's external dimensions. The device effectively alleviates nonlinear issues associated with gaps in the fin system and enhances both the dynamic and static stiffness of the folding fin. A parametric design model for the gap elimination device has been developed, delineating the relationship between the structure and layout of the SMA columns, the actuation temperature, load, and the target gap for elimination. We conducted static load tests along with modal tests at room and elevated temperatures to evaluate the stiffness enhancement performance of the folding fin before and after gap elimination. The experiments verified that the designed gap elimination device significantly enhances both the static and dynamic stiffness of the folding fin. Additionally, the first-order frequency of the folding fin increased by 40 % at room temperature and by 36.7 % at 200 °C. This paper provides quantifiable guidance for the structural and parametric design of gap elimination devices in folding fins. Optimal structural parameters, determined based on aerodynamic loads and gap elimination requirements, enhance the stiffness of the folding fin, thus improving the aircraft's flight performance. © 2025

关键词： Freewing aircraft

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Cross-Subject Depression Level Classification Using EEG Signals with a Sample Confidence Method

arXiv

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arXiv 2025年

作者： Zhang, Zhong-Yi Xu, Chen-Yang Zhao, Li-Xuan Hou, Hui-Rang Meng, Qing-Hao Tianjin Key Laboratory of Process Measurement and Control Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin300072 China

Electroencephalogram (EEG) is a non-invasive tool for real-time neural monitoring, widely used in depression detection via deep learning. However, existing models primarily focus on binary classification (depression/normal), lacking granularity for severity assessment. To address this, we proposed the DepL-GCN, i.e., Depression Level classification based on GCN model. This model tackles two key challenges: (1) subjectivity in depression-level labeling due to patient self-report biases, and (2) class imbalance across severity categories. Inspired by the model learning patterns, we introduced two novel modules: the sample confidence module and the minority sample penalty module. The former leverages the L2-norm of prediction errors to progressively filter EEG samples with weak label alignment during training, thereby reducing the impact of subjectivity;the latter automatically upweights misclassified minority-class samples to address imbalance issues. After testing on two public EEG datasets, DepL-GCN achieved accuracies of 81.13% and 81.36% for multi-class severity recognition, outperforming baseline models. Ablation studies confirmed both modules’ contributions. We further discussed the strengths and limitations of regression-based models for depression-level recognition. Copyright © 2025, The Authors. All rights reserved.

关键词： Electroencephalography

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Methodology of Designing and Modeling Projects for robotics and Mechatronics Course of Intelligent robotics Master Program

Methodology of Designing and Modeling Projects for Robotics ...

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Educational Innovation (ECEI), IEEE Eurasian Conference on

作者： Shifa Sulaiman Alexander Eryomin Tatyana Tsoy Evgeni Magid Laboratory of Intelligent Robotics Systems (LIRS) Institute of Information Technology and Intelligent Systems Kazan Federal University Kazan Russia School of Electronic Engineering HSE University Moscow Russia

Intelligent robots are employed in a variety of sectors due to their capability to carry out tasks autonomously. As a response to the growing importance of intelligent robots, a new master’s program in intelligent robotics was introduced by Kazan Federal University, Russia in 2017. It was created by analyzing the curricula of leading robotics universities worldwide. The main objective of this master’s program is to provide in-depth knowledge to students regarding intelligent robots’ development and applications. Classes of the program were conducted by combining theoretical lectures with applications of robotics software and hardware tools. Computer-aided design (CAD) software and Robotic Operating System (ROS) libraries were practiced by students in courses. We present an approach for designing and modeling projects within the robotics and Mechatronics course for first-year students using SOLIDWORKS and ROS. Educational methodologies adopted by a student are presented in this article as a case study of an elevator-operating robot.

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State-of-Charge (SOC) Estimation of Lithium-Ion Battery Based on Unscented Kalman Filtering 6

State-of-Charge (SOC) Estimation of Lithium-Ion Battery Base...

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6th IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2024

作者： Miao, Mengfan Li, Ligang Wang, Zhongfeng Jiang, Jing Shenyang Ligong University College of Automation and Electrical Engineering Liaoning China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China

ISBN: (纸本)9798350316520

Real-time estimation of State of Charge (SOC) for lithium-ion batteries is one of the core technologies in Battery Management systems (BMS). Accurate SOC estimation is fundamental for managing lithium-ion batteries. In this study, a second-order RC equivalent circuit model is established, and parameter identification methods are employed to determine the model parameters. The identified parameters are then incorporated back into the second-order RC model. The accuracy of these parameters and the model is validated through Hybrid Pulse Power Characteristic (HPPC) tests. Finally, the Unscented Kalman Filtering algorithm (UKF) is utilized to estimate battery SOC. Experimental results demonstrate that SOC estimation based on UKF exhibits high precision and stability. © 2024 IEEE.

关键词： Lithium-ion batteries

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Trajectory Planning Towards Water-Air Trans-Media Motion for Robotic Dolphin

Trajectory Planning Towards Water-Air Trans-Media Motion for...

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2024 China Automation Congress, CAC 2024

作者： Xiong, Yan Zhang, Pengfei Chen, Di Yu, Junzhi State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China Shandong Nuclear Power Company LTD Yantai265116 China School of Intelligence Science and Technology University of Science and Technology Beijing Beijing100083 China

ISBN: (纸本)9798350368604

Water-air trans-media navigators have multi-media motion modes, breaking through the limitation that traditional robots can only operate in a single medium. Autonomous navigation is an indispensable component of the process of trans-media motion. Most of the current work has only completed the development and testing of prototypes, and the problem of task-oriented motion planning and control needs to be solved. In this paper, a safe and efficient hierarchical approach is proposed. First, a novel rapidly exploring random tree-based algorithm is proposed to search for a suitable path. Then, by fixing bound waypoints, the time-optimization trajectory is planned. Finally, the trajectory tracker is designed based on nonlinear model predictive control (NMPC). Simulation experiments numerically validate the proposed method, offering some new insights for further trans-media motions. © 2024 IEEE.

关键词： Trajectories

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Quantitative Analysis of Ankle Spasticity Through Electromyography Signal

Quantitative Analysis of Ankle Spasticity Through Electromyo...

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Medical Technologies National Conference (TIPTEKNO)

作者： Ayse Gurluk Hafiz Muhammad Bilal Elif Hocaoglu Living Robotics Laboratory Graduate School of Health Sciences Physiotherapy and Rehabilitation Program Istanbul Medipol University Istanbul Türkiye Living Robotics Laboratory Graduate School of Engineering and Natural Sciences Electrical-Electronics Engineering and Cyber-Systems Program Istanbul Medipol University Istanbul Türkiye Department of Electrical and Electronics Engineering Living Robotics Laboratory Istanbul Medipol University Istanbul Türkiye

ISBN: (数字)9798331529819

ISBN: (纸本)9798331529826

This study presents a more accurate evaluation method for assessing ankle spasticity compared to conventional goniometric techniques by utilizing measurements obtained from Inertial Measurement Units (IMU) and surface electromyography (sEMG) devices. Integrating IMU and EMG sensors provides substantial benefits for accurately determining the range of motion (ROM) associated with spasticity during targeted movements. In this study, the proposed method provides precise measurement and an objective evaluation of onset time detection of antagonistic muscle co-contraction, and accordingly the ROM of the actuated joint. Moreover, the implementation of cost-effective wearable sensors enables the monitoring of muscle spasticity in clinical environments and can be particularly valuable in regions with limited access to experienced therapists, providing a more efficient approach to tracking spasticity levels.

关键词： Ankle Measurement units Inertial navigation Muscles Electromyography Sensors Reliability Motion control Read only memory Monitoring

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Learn to Coordinate: A Whole-Body Learning from Demonstration Framework for Differential Drive Mobile Manipulators

Learn to Coordinate: A Whole-Body Learning from Demonstratio...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Yang, Yuqiang Huang, Darong Chen, Chen Zeng, Chao He, Yanong Yang, Chenguang South China University of Technology Automation Science and Engineering Guangzhou China Application Innovate Laboratory Huawei Technologies Co. Ltd Shenzhen China Universitat Hamburg Technical Aspects of Multimodal Systems Hamburg Germany Bristol Robotics Laboratory University of the West of England Bristol United Kingdom

ISBN: (纸本)9798350337020

This paper proposes a whole-body learning from demonstration (LfD) framework that enables differential drive mobile manipulators to learn coordination working and disturbance rejection. First, an efficient kinesthetic teaching method is devised based on the weighted least-norm (WLN) inverse kinematics solution and an admittance controller, which facilitates human users to guide the mobile manipulator to perform tasks. Second, we propose a whole-body LfD framework through Gaussian Process, which endows the mobile manipulator's skill learning process with features of large-scale convergence, coordination working and disturbance rejection, after just a few human demonstrations. The proposed learning framework also allows for human-in-the-loop correction when the whole-body is conducting a task. Finally, the effectiveness of the proposed framework is verified via two simulations and a pick-and-place experiment. Supplementary video for this paper is available in github https://***/yuqiang-yang/SMC2023-Video. © 2023 IEEE.

关键词： Gaussian Process Learning from Demonstration Wholebody Control

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