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作者： Olaya Álvarez-Tuñón Luiza Ribeiro Marnet Martin Aubard László Antal Maria Costa Yury Brodskiy Department of Electrical and Computer Engineering Artificial Intelligence in Robotics Laboratory (AiR-Lab) Aarhus University Aarhus C Denmark EIVA a/s Skanderborg Denmark OceanScan Marine Systems & Technology Matosinhos Portugal RWTH Aachen University Aachen Germany

ISBN: (数字)9798350362077

ISBN: (纸本)9798350362084

This paper presents SubPipe, an underwater dataset for SLAM, object detection, and image segmentation. SubPipe has been recorded using a lightweight autonomous underwater vehicle (LAUV), operated by OceanScan MST, and carrying a sensor suite including two cameras, a side-scan sonar, and an inertial navigation system, among other sensors. The AUV has been deployed in a pipeline inspection environment with a submarine pipe partially covered by sand. The AUV's pose ground truth is estimated from the navigation sensors. The side-scan sonar and RGB images include object detection and segmentation annotations, respectively. State-of-the-art segmentation, object detection, and SLAM methods are benchmarked on SubPipe to demonstrate the dataset's challenges and opportunities for leveraging computer vision algorithms. To the authors' knowledge, this is the first anno-tated underwater dataset providing a real pipeline inspection scenario. The dataset and experiments are publicly avail-able online at https://***/remaro-network/SubPipe-dataset.

关键词： Location awareness Image segmentation Simultaneous localization and mapping Oceans Pipelines Object detection Inertial navigation

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Optimal Vision-Based Orientation Steering Control for a 3D Printed Dexterous Snake-Like Manipulator to Assist Teleoperation

TechRxiv

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TechRxiv 2023年

作者： Razjigaev, Andrew Pandey, Ajay K. Howard, David Roberts, Jonathan Jaiprakash, Anjali Crawford, Ross Wu, Liao The School of Electrical Engineering and Robotics The QUT Centre for Robotics Brisbane Australia The Cyber Physical Systems Program Data61 CSIRO Australia The Department of Orthopaedic Surgery Prince Charles Hospital ChermsideQLD Australia The School of Mechanical and Manufacturing Engineering University of New South Wales Sydney Australia

Endoscopic cameras attached to miniaturised snakelike continuum robotic arms can improve dexterity, accessibility, and visibility in minimally invasive surgical tasks. This steerable camera can expand the field of view and enhance the surgical experience with additional degrees of freedom. However, it also creates more control options that complicate human-machine interaction. This challenge presents an opportunity to develop novel human-machine control strategies using visual sensing to complement the dexterous actuation of a steerable surgical manipulator. This study presents a semi-autonomous controller to assist teleoperation by steering a camera such that it keeps an arbitrary target in the centre of the field of view, thus assisting in surveying different orientations about the target with image-based information. Two controllers are proposed using classical image-based visual servoing techniques and optimal visual predictive control techniques. These techniques are simulated and validated on our robot SnakeRaven: a 3D-printed patient-specific end-effector attached to the RAVEN II surgical platform. Both systems, most notably the visual predictive approach, operated successfully with robustness to a lack of information about the target. A video demonstrating the main results of this paper can be found via https://***/fiUM9qYdl1U © 2023, CC BY.

关键词： Remote control

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Modular Cyber-Physical System for Smart Industry: a case study on energy load disaggregation

Modular Cyber-Physical System for Smart Industry: a case stu...

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International Conference on Control, Automation and Diagnosis (ICCAD)

作者： Jorge Alves Pedro Sousa Bárbara Matos Jérôme Mendes Francisco Souza Tiago Matias Department of Electrical and Computer Engineering University of Coimbra Institute of Systems and Robotics Coimbra Portugal Oncontrol Technologies Coimbra Portugal Dept. Analytical Chemistry & Chemometrics Radboud University Nijmegen AJ Netherlands

Constant changes have marked the industry, and cyber-physical systems have offered great potential in Industry 4.0 on production processes, allowing the integration of computational intelligence and real-time processing. In this context, this paper proposes a modular hardware system for industrial applications according to a plug & play concept. The proposed system comprises a processing module (mPP) and specific expansion modules (mEXs). The mPP is responsible for administrating the network/communication. It collects data from the mEXs, extracts features, processes the features through artificial intelligence, and interacts with the production process. The mEXs comprise sensors, conditioning circuits, and an analog/digital converter. They are responsible for acquiring field signals and their transmission to the mPP. The proposed system is designed for operating with electrical protection, allowing reliable operation of the mPP and mEXs. For evaluating and demonstrating the proposed system in a real scenario, we applied it in a case study for non-intrusive energy load disaggregation.

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Tracking the Dynamic Neural Connectivity via Conjugate Gradient Optimization*

Tracking the Dynamic Neural Connectivity via Conjugate Gradi...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Mingdong Li Shuhang Chen Zhijia Zhao Yiwen Wang Robotics and Autonomous Systems Thrust The Hong Kong University of Science and Technology (Guangzhou) Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology School of Mechanical and Electrical Engineering Guangzhou University Department of Electronic and Computer Engineering The Department of Chemical and Biological Engineering The Hong Kong University of Science and Technology

Neural connectivity describes how neuron populations coordinate and create cognitive and behavioral functions. Neural connectivity performs dynamics where its population spiking responses to stimuli or intention change over time. Brain-machine interface (BMI) provides a framework for studying dynamical neural connectivity. In BMI, point process is a powerful technique in analyzing the single neuronal tuning. And generalized linear mode (GLM) as an encoding model can incorporate the tuning in kinematics and the neural connectivity. Quantification and tracking of dynamic neural connectivity can contribute to the elucidation of the generation of brain functions in a computational way. However, most of the previous work focused on single neuronal adaptation to kinematics. When a neuron is significantly modulated by some other neurons in some tasks, the shape of the log likelihood function for single neuronal observations can be narrowed in some dimensions. And the existing gradient-based methods are not able to reach the optimum in a fast and adaptive searching way. In this work, to maximize the likelihood of observations and obtain the dynamic neural connectivity tuning parameters, we proposed a conjugate gradient-based encoding model (CGE). We illustrate CGE for likelihood function using the real experimental data under manual control and brain control. The results show that the proposed CGE has better performance in tracking the dynamic neural connectivity tuning parameters and modeling neural *** Relevance— Not directly related.

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Transcranial Direct Current Stimulation Associated with Visual and Auditory Cueing during Gait Training: A Case Study with a Parkinson's Disease Patient

Transcranial Direct Current Stimulation Associated with Visu...

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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： Angie Pino Patricio Barria Karim Baleta Rolando Aguilar José M. Azorín Marcela Múnera Carlos A. Cifuentes Club de Leones Cruz del Sur Rehabilitation Center Punta Arenas Chile Department of Electrical Engineering University of Magallanes Punta Arenas Chile Department of Systems Engineering and Automation Miguel Hernández University of Elche Elche Spain Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Parkinson's Disease (PD) is a neurodegenerative disorder that leads to motor dysfunctions and restricts walking independence. Approaches such as transcranial direct current stimulation (tDCS) and cueing gait are potential rehabilitation strategies that have proven efficient in improving motor function in individuals with PD in preliminary and separate studies. This case study with a single PD patient explores the feasibility and potential effects of combining anodal tDCS (a-tDCS) with visual and auditory cues during 15 gait training sessions. The patient was assessed before the first intervention and after completing all training weeks regarding kinematic parameters of gait, neuronal activation, muscle strength, and functional skills. Results showed a beneficial impact in significantly increasing the participant's speed, stride length, step length, and muscle strength. Furthermore, the decrease in beta brain activity and increase in the delta were associated with a reduction in the effects of the disease, improved motor performance, and shorter functional task times. This study suggests the a-tDCS strategy with double cueing gait can lead to therapeutic potential in relieving the disease's motor symptoms.

关键词： Training Visualization Motor drives Parkinson's disease Kinematics Muscles Motors Neurorehabilitation Transcranial direct current stimulation Robots

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Nanoplasmonic Biosensor for Cytokine Profiling in Patient Plasma 22

Nanoplasmonic Biosensor for Cytokine Profiling in Patient Pl...

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22nd International Conference on Solid-State Sensors, Actuators and Microsystems, Transducers 2023

作者： Chin, Lip Ket Im, Hyungsoon Park, Sung-Gyu Chousterman, Benjamin City University Of Hong Kong Department Of Electrical Engineering Kowloon Hong Kong Massachusetts General Hospital Center For Systems Biology MA02114 United States Korea Institute Of Materials Science Department Of Nano-Bio Convergence Changwon51508 Korea Republic of Hôpital Lariboisière Département d'Anesthésie-Réanimation Paris75010 France

ISBN: (纸本)9784886864352

Molecular analysis has been widely used for disease diagnosis and treatment efficacy analysis. Plasmonic biosensors are popular for molecular analysis because of their rapid detection and high sensitivity. This paper presents a nanoplasmonic biosensor combined with a chemifluorescence approach for multiplex molecular profiling in plasma samples. The nanoplasmonic biosensor significantly improves the detection sensitivity with the fluorescence signal being enhanced by ~300-fold. In the measurement of multiple cytokines' expression levels in patient plasma, the experimental results show that the nanoplasmonic biosensor achieves a limit of detection as low as 0.5 pg/mL. The assay time is as fast as 1 hour. We envisage that the developed nanoplasmonic biosensor has broad applications in disease diagnosis, including inflammation, cancer, or even infectious diseases. © 2023 IEEJ.

关键词： biosensors cytokine molecular profiling Nanoplasmonics

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Contact Consistent Disturbance Estimation for Quadruped Robots

Contact Consistent Disturbance Estimation for Quadruped Robo...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Hasan Can Özden Emre Tanfener Hasan Eftun Orhon Ömer Tarık Banuş Uluç Saranlı Mert Ankaralı Ali Emre Turgut Mechanical Engineering Department Middle East Technical University Ankara Turkey Defense Systems Technologies Division Aselsan Inc Ankara Turkey Center for Robotics and AI Middle East Technical University Ankara Turkey Computer Engineering Department Middle East Technical University Ankara Turkey Electrical and Electronics Engineering Department Middle East Technical University Ankara Turkey

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Quadrupedal locomotion in environments without visual aid presents significant challenges in achieving automation capabilities. Often relying solely on IMU sensors and proprioceptive feedback from motors due to limited visual perception, understanding the robot’s interaction with its environment becomes crucial for safe and efficient navigation. This paper presents a novel approach for estimating external forces applied to a quadrupedal robot’s body, a critical aspect of its interaction with the environment. Our method integrates generalized momentum methods, contact constraints, and inertial measurement unit (IMU) data to accurately estimate these external forces. By using these diverse sources of information, the output of this work can enable navigation algorithms to enhance the robot’s ability to navigate complex environments, improving stability and adaptability. Simulation studies and experimental validations demonstrate the effectiveness of the proposed method in real-world scenarios, highlighting its potential for advancing quadrupedal locomotion in unfamiliar terrains where visual aids are limited.

关键词： Visualization Measurement units Automation Heuristic algorithms Loading Dynamics Estimation Inertial navigation Quadrupedal robots Collision avoidance

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Multiplier analysis of Lurye systems with power signals

Multiplier analysis of Lurye systems with power signals

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IEEE Conference on Decision and Control

作者： William P. Heath Joaquin Carrasco School of Computer Science and Engineering Bangor University Dean St LL57 1UT UK Department of Electrical and Electronic Engineering Control Systems and Robotics Group Nancy Rothwell Building University of Manchester M13 9PL UK

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Multipliers can be used to guarantee both the Lyapunov stability and input-output stability of Lurye systems with time-invariant memoryless slope-restricted nonlinearities. If a dynamic multiplier is used there is no guarantee the closedloop system has finite incremental gain. It has been suggested in the literature that without this guarantee such a system may be critically sensitive to time-varying exogenous signals including noise. We show that multipliers guarantee the power gain of the system to be bounded and quantifiable. Furthermore power may be measured about an appropriate steady state bias term, provided the multiplier does not require the nonlinearity to be odd. Hence dynamic multipliers can be used to guarantee Lurye systems have low sensitivity to noise, provided other exogenous systems have constant steady state. We illustrate the analysis with an example where the exogenous signal is a power signal with non-zero mean.

关键词： Sensitivity Power measurement Noise Stability analysis Steady-state Time-varying systems Lyapunov methods

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Software Tools for Signal and Data Analysis Using LabView Platform

Software Tools for Signal and Data Analysis Using LabView Pl...

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International Symposium on Fundamentals of electrical engineering (ISFEE)

作者： Cerasela Camui Liviu Popescu Viorel Petre George Constantin Faculty of Electrical Engineering National University of Science and Technology Politehnica Bucharest Romanaia Department of Electrical Machines Materials and Drives Faculty of Electrical Engineering National University of Science and Technology Politehnica Bucharest Romanaia Department of Measurements Electrical Devices and Static Converters National University of Science and Technology Politehnica Bucharest Romanaia Department Machine and Production Systems Faculty of Industrial Engineering and Robotics National University of Science and Technology Politehnica Bucharest Romanaia

ISBN: (数字)9798350308563

ISBN: (纸本)9798350308570

The solutions for the computerized integration, control and management of all the (vital) functions of some technical installations, aim to reduce administrative and maintenance costs, to increase the efficiency and comfort of the occupants and to improve business performance in general. Signal processing is one of the most studied domains as, in real life, the distances between the signal generation and the decision unit can be important. Also, the generation of the signal at the source is not without additional noise. For example, when controlling electric powertrains, this noise can be a source of errors. The possibility of creating commands that destabilize the vehicle is not far off. In this context, the present paper proposes few ways, tools and examples that are able to generate signals and noises. The result is displayed to observe signal evolution without or with the influence of other processes. The examples are built using National Instruments' graphical programming environment, LabVIEW.

关键词： Data analysis Noise Process control Phase control Mechanical power transmission Signal generators Real-time systems

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Marker Correspondence Initialization in an IR Motion Capturing System

Marker Correspondence Initialization in an IR Motion Capturi...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： M. M. Kalantari R. Khorrambakht M. R. Dindarloo S. A. Khalilpour H. D. Taghirad P. Cardou Advanced Robotics and Automated Systems (ARAS) Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Mechanical Engineering Robotics Laboratory Laval University Quebec City Canada

ISBN: (纸本)9781665454537

Marker-based motion capturing (MoCap) systems are of great importance among the different visual referencing systems, because of their robustness, speed, and precision. Due to the lack of highly descriptive visual features in captured images in such systems, establishing the correspondences between the multi-view observations of the markers is a major challenge. This problem is even more challenging when there is no preceding or low reliable data on the markers’ positions. Under these conditions, the correspondences have to be found from a large space of possible matches. This paper aims to provide a solution for this correspondence initialization problem in multi-view tracking systems based on graph theory and Girvan-Newman community detection. The validity and robustness of the algorithm are verified via experimental analysis.

关键词： Visualization Mechatronics Tracking Reliability theory Robustness Graph theory Robots

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