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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Huijie Dong Chunyang Zhao Tiezhu Qiao Jian Wang Di Chen Yan Meng Junzhi Yu Ministry of Education Key Laboratory of Advanced Transducers and Intelligent Control System Taiyuan University of Technology Taiyuan China Institute of Automation Laboratory of Cognitive and Decision Intelligence for Complex System Chinese Academy of Sciences Beijing China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China College of Electronics and Information Engineering Guangdong Ocean University Zhanjiang China

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named ‘CourierFish’. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks.

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Robust MPC for networks with varying communication capabilities

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IFAC-PapersOnLine 2021年第6期54卷 20-27页

作者： Markus Kögel Daniel Quevedo Rolf Findeisen Laboratory for Systems Theory and Automatic Control Otto-von-Guericke University Magdeburg Germany School of Electrical Engineering and Robotics Queensland University of Technology Brisbane Australia

We consider the control of constrained, uncertain systems over wireless communication networks with varying capabilities. We focus on the case that a radio resource manager, which manages the wireless network, provides guaranteed minimum communication at fixed time instants while offering more frequent communication depending on the current load of the shared network, available network capacity or other conditions. To exploit the additionally available communication we propose a robust model predictive control strategy exploiting ideas of tube MPC that utilizes the possibly additionally available communication to improve the closed loop performance. Conditions to guarantee closed loop properties are presented. Simulations illustrate the proposed approach and its benefits.

关键词： Networked control systems Control over wireless networks Robust Model Predictive Control Tube based MPC Internet of things Cyber-physical systems

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Robotic Intracellular Electrochemical Sensing for Adherent Cells

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Cyborg and Bionic systems 2022年第1期2022卷 75-86页

作者： Weikang Hu Yanmei Ma Zhen Zhan Danish Hussain Chengzhi Hu Shenzhen Key Laboratoryof Biomimetic Robotisand Intlligent Systems Department of Mechanicaland Enery EngineeringSouthern University of Science and TechnologyShenzhenChina Department of Mechatronics Engineering National University of Sciences and TechnologyIslamabadPakistan Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern Universityof Science and TechnologyShenzhenChina

Nanopipette-based observation of intracellular biochemical processes is an important approach to revealing the intrinsic char acteristics and heterogeneity of cells for better investigation of disease progression or early disease ***,the manual operation needs a skilled operator and faces problems such as low throughput and poor *** paper proposes an automated nanopipette-based microoperation system for cell detection,*** nonovershoot positioning of the nanopipette tip in proximity to the cell of interest,cell approaching and proximity detection between nanopipette tip and cell surface,and cell penetration and detection of the intracellular reactive oxygen species(ROS).A robust focus algorithm based on the number of cell contours was proposed for adherent cells,which have sharp peaks while retaining *** automated detection of adherent cells was evaluated on human umbilical cord vein endothelial cells(HUVEC)and NIH/3T3 cells,which provided an average of 95.65%true-positive rate(TPR)and 7.59%false-positive rate(FPR)for in-plane cell *** three dimensional nonovershoot tip positioning of the nanopipette was achieved by template matching and evaluated under the interference of *** current feedback was employed for the proximity detection between the nanopipette tip and cell ***,cell penetration and electrochemical detection of ROS were demonstrated on human breast cancer cells and zebrafish embryo *** work provides a systematic approach for automated intracellular sensing for adherent cells,laying a solid foundation for high-throughput detection,diagnosis,and classification of different forms of biochemical reactions within single cells.

关键词： diagnosis proximity retaining

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Motor speed estimation and failure detection of a small UAV using density of maxima

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Frontiers of Information Technology & Electronic engineering 2021年第7期22卷 1002-1009页

作者： Jefferson S.SOUZA Moises C.BEZERRIL Mateus A.SILVA Frank C.VERAS Abel LIMA-FILHO Jorge Gabriel RAMOS Alisson V.BRITO Laboratory of System Engineering and Robotics Federal University of ParaibaJoao PessoaBrazil Department of Information Systems Federal University of PiauiPicosBrazil Department of Mechanical Engineering Federal University of ParaibaJoao PessoaBrazil Department of Physics Federal University of ParaibaJoao PessoaBrazil

This work presents the application of the technique named signal analysis based on chaos using density of maxima to analyze brushless direct current *** uses a correlation coefficient estimated from the density of maxima of the current *** study demonstrates in experiments the speed estimation of a brushless motor on a testbench and failure detection in a small flying *** experimental results demonstrate that it is possible to estimate the speed in 97.8%of the cases and to detect failure in 82.75%of the analyzed cases.

关键词： Unmanned aerial vehicle(UAV) Speed identification Failure detection Chaos

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Enhancing Knee Rehabilitation Exoskeleton Control via a Robust LMI-Based Strategy and by Considering State Constraints

Enhancing Knee Rehabilitation Exoskeleton Control via a Robu...

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International Conference on systems and Control (ICSC)

作者： Sahar Jenhani Hassène Gritli Laboratory of Robotics Informatics and Complex Systems (RISC Lab - LR16ES07) National Engineering School of Tunis University of Tunis El Manar Tunis Tunisia Higher Institute of Information and Communication Technologies University of Carthage Tunis Tunisia RISC Lab.

This study introduces a robust control strategy to regulate the position of knee rehabilitation exoskeleton robot. A description of this particular robotic system and its nonlinear dynamic model are outlined first. The system faces challenges such as state constraints, external disruptions, and parameter uncertainties, all of which are meticulously addressed in the control design. Subsequently, we define the affine state-feedback controller and its design based on the LMI approach, aimed at ensuring the stabilization of the active exoskeleton robotic system at the knee joint level and hence its stability at the desired position. To achieve this, our proposed method utilizes a quadratic Lyapunov function and leverages mathematical tools such as the S-procedure Lemma, the Schur complement, the matrix inversion Lemma, and the Young inequality to derive finally two LMI conditions that guarantee the stability of the controlled knee exoskeleton system. Finally, the simulation studies validate the effectiveness of the proposed approach in the design of the LMI stability condition and hence the efficiency of the controller in the robust control of the knee exoskeleton robot.

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Photovoltaic Arrays’ Dynamic Model Parameter Estimation

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IFAC-PapersOnLine 2023年第2期56卷 6845-6850页

作者： Alexey Bobtsov Fernando Mancilla-David Stanislav Aranovskiy Romeo Ortega Faculty of Control Systems and Robotics ITMO University 197101 Saint Petersburg Russia Laboratory “Control of Complex Systems” Institute of Problems of Mechanical Engineering V.O. Bolshoj pr. 61 St. Petersburg 199178 Russia University of Colorado Denver Denver Colorado 80204 USA IETR – CentaleSupélec Cesson-Sévigné France Departamento Académico de Sistemas Digitales ITAM México

This paper deals with the problem of on-line identification of the parameters of a realistic dynamical model of a photovoltaic array connected to a power system through a power converter. It has been shown in the literature that, when interacting with switching devices, this model is able to better account for the PV array operation, as compared to the classical five parameter static model of the array. While there are many results of identification of the parameters of the latter model, to the best of our knowledge, no one has provided a solution for the aforementioned more complex dynamic model since it concerns the parameter estimation of a nonlinear, underexcited system with unmeasurable state variables. Achieving such objective is the main contribution of the paper. We propose a new parameterisation of the dynamic model, which, combined with the powerful identification technique of dynamic regressor extension and mixing, ensures a fast and accurate online estimation of the unknown parameters. Realistic numerical examples via computer simulations are presented to assess the performance of the proposed approach—even being able to track the parameter variations when the system changes operating point.

关键词： photovoltaic arrays on-line parameter estimation identification of nonlinear systems

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A smart wearable device for capturing biomechanical energy from human knee motion

A smart wearable device for capturing biomechanical energy f...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Hugo Hung-Tin Chan Haisu Liao Xuan Zhao Junrui Liang Wei-Hsin Liao Xinyu Wu Fei Gao Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin Hong Kong China School of Information Science and Technology ShanghaiTech University Shanghai China

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

Sustainable power supply is a challenge for portable and wearable electronic devices such as cell phones and headsets. To address this, researchers proposed capturing biomechanical energy from human motion to generate electricity. This paper proposed and developed a lightweight wearable device to capture the biomechanical energy from the human knee motion. To reduce the effect of inertial force on human gait, we developed a lightweight and compact transmission chain to convert the bidirectional rotation of the knee to a unidirectional rotation of the generator. Two input bevel gears with opposite one-way bearings on the same shaft are engaged with a single output bevel gear of the generator thereby only one input bevel gear is engaged for each input direction, achieving unidirectional output. In addition, to reduce velocity fluctuation and further minimize the effect of inertial force, a flywheel was fixed to the motor shaft via a gearbox. A prototype of the wearable device was developed and tested on a subject walking on a treadmill. Experimental results shows the flywheel enabled the harvester to achieve a continuous output while halving voltage fluctuations compared to a conventional harvester. The harvesters average power output can reach 0.11 W with minimal effects on the subject’s walking gait.

关键词： Knee Legged locomotion Biomechanics Shafts Fluctuations Voltage fluctuations Torque

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Feature-based Event Stereo Visual Odometry

Feature-based Event Stereo Visual Odometry

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European Conference on Mobile Robots (ECMR)

作者： Antea Hadviger Igor Cvišić Ivan Marković Sacha Vražić Ivan Petrović Laboratory for Autonomous Systems and Mobile Robotics University of Zagreb Faculty of Electrical Engineering and Computing Croatia Rimac Automobili Croatia

Event-based cameras are biologically inspired sensors that output events, i.e., asynchronous pixel-wise brightness changes in the scene. Their high dynamic range and temporal resolution of a microsecond makes them more reliable than standard cameras in environments of challenging illumination and in high-speed scenarios, thus developing odometry algorithms based solely on event cameras offers exciting new possibilities for autonomous systems and robots. In this paper, we propose a novel stereo visual odometry method for event cameras based on feature detection and matching with careful feature management, while pose estimation is done by feature reprojection error minimization. We evaluate the performance of the proposed method on two publicly available datasets: MVSEC sequences captured by an indoor flying drone and DSEC outdoor driving sequences. MVSEC offers accurate ground truth from motion capture, while for DSEC, which does not offer ground truth, in order to obtain a reference trajectory on the standard camera frames we used our SOFT visual odometry, one of the highest ranking algorithms on the KITTI scoreboards. We compared our method to the ESVO method, which is the first and still the only stereo event odometry method, showing on par performance on both MVSEC and DSEC sequences. Furthermore, two important advantages of our method over ESVO are that it adapts tracking frequency to the asynchronous event rate and does not require initialization.

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Recursive Joint Cramér-Rao Lower Bound for Nonlinear Parametric systems with Colored Noise

Recursive Joint Cramér-Rao Lower Bound for Nonlinear Parame...

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International Conference on Information Fusion

作者： Xianqing Li Zhansheng Duan Uwe D. Hanebeck Center for Information Engineering Science Research Xi&#x0027 an Jiaotong University Xi&#x0027 an Shaanxi China Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology (KIT) Germany

ISBN: (数字)9781737749721

ISBN: (纸本)9781665489416

The performance evaluation for joint state and parameter estimation (JSPE) is of great significance. Joint Cramér-Rao lower bound (JCRLB) has been widely studied for JSPE of nonlinear parametric systems with white noise. However, in practice, the noise is often colored due to high measurement frequency and bandlimited signal channels. In this paper, a recursive JCRLB is developed for JSPE of nonlinear parametric systems with colored noise, characterized by auto-regressive (AR) models. First, we propose a unified recursive JCRLB for JSPE of general nonlinear parametric systems with higher-order autocorrelated process noises and autocorrelated measurement noise simultaneously. Then its relationship with the posterior Cramér-Rao lower bound (PCRLB) for filtering of nonlinear systems with colored noise and the hybrid Cramér-Rao lower bound (HCRLB) for JSPE of regular parametric systems with white noise are provided. Illustrative examples in radar target tracking verify the effectiveness of the proposed JCRLB for the performance evaluation for JSPE of nonlinear parametric systems with colored noise.

关键词： Performance evaluation Target tracking Parameter estimation Filtering White noise Radar tracking Frequency measurement

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Soft yet Effective Robots via Holistic Co-Design

arXiv

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arXiv 2025年

作者： Stölzle, Maximilian Pagliarani, Niccolò Stella, Francesco Hughes, Josie Laschi, Cecilia Rus, Daniela Cianchetti, Matteo Santina, Cosimo Della Zardini, Gioele Laboratory for Information & Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States Cognitive Robotics Delft University of Technology Mekelweg 2 CD Delft2628 Netherlands The BioRobotics Institute Scuola Superiore Sant’Anna Pisa56025 Italy Embodied AI AG Lausanne1015 Switzerland CREATE Lab EPFL Lausanne1015 Switzerland Advanced Robotics Centre Department of Mechanical Engineering National University of Singapore 117575 Singapore Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology CambridgeMA02139 United States

Soft robots promise inherent safety via their material compliance for seamless interactions with humans or delicate environments. Yet, their development is challenging because it requires integrating materials, geometry, actuation, and autonomy into complex mechatronic systems. Despite progress, the field struggles to balance task-specific performance with broader factors like durability and manufacturability—a difficulty that we find is compounded by traditional sequential design processes with their lack of feedback loops. In this perspective, we review emerging co-design approaches that simultaneously optimize the body and brain, enabling the discovery of unconventional designs highly tailored to the given tasks. We then identify three key shortcomings that limit the broader adoption of such co-design methods within the soft robotics domain. First, many rely on simulation-based evaluations focusing on a single metric, while real-world designs must satisfy diverse criteria. Second, current methods emphasize computational modeling without ensuring feasible realization, risking sim-to-real performance gaps. Third, high computational demands limit the exploration of the complete design space. Finally, we propose a holistic co-design framework that addresses these challenges by incorporating a broader range of design values, integrating real-world prototyping to refine evaluations, and boosting efficiency through surrogate metrics and model-based control strategies. This holistic framework, by simultaneously optimizing functionality, durability, and manufacturability, has the potential to enhance reliability and foster broader acceptance of soft robotics, transforming human-robot interactions. © 2025, CC BY.

关键词： Intellectual property core

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