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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Marcos S. Pereira Luciano C. A. Pimenta Bruno V. Adorno Graduate Program in Electrical Engineering Department of Electronic Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Manchester Centre for Robotics and AI The University of Manchester Manchester UK

This paper proposes a task planning and motion control framework that generates task plans for a linear temporal logic specification (LTL), which are then executed using a task-space constrained motion controller and a local task planner that overcomes local minima. We propose a new encoding for task specifications, directly in the task-space, as constraints of a mixed-integer linear program that can be used with off-the-shelf LTL linear encoding. We apply our framework to plan and execute trajectories for a free-flying robot and show that the task plan is accomplished without collisions, even in the presence of unexpected moving obstacles that are not considered in the planning phase, while control signal constraints are satisfied. To evaluate the local minima avoidance, we compare the local task planner with a sampling-based motion planner, and the results show a smoother trajectory with a faster execution and less total planning time when using our framework. Last, our framework scaled well with a longer LTL specification, as opposed to automata-based frameworks that usually suffer with the curse of the dimensionality.

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Enhancing Localized Surface Plasmon Resonance Response for Albumin Detection by Optimizing the Lateral Size of Hexagonal Gold Nanoparticles

Enhancing Localized Surface Plasmon Resonance Response for A...

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IEEE International Conference on Semiconductor Electronics (ICSE)

作者： Silva Nurfasha Chandra Wulandari Lilik Hasanah Ahmad Aminuddin Yanurita Dwi Hapsari Mohammad Arifin Roer Eka Pawinanto Budi Mulyanti Study Program of Physics Universitas Pendidikan Indonesia Bandung Indonesia Study Program of Physics Institut Teknologi Bandung Bandung Indonesia Department of Physics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Surabaya Indonesia Study Program of Industrial Automation and Robotics Engineering Education Universitas Pendidikan Indonesia Bandung Indonesia Study Program of Electrical Engineering Universitas Pendidikan Indonesia Bandung Indonesia

ISBN: (数字)9798350378313

ISBN: (纸本)9798350378320

The kidney is a human organ with numerous vital functions, mainly for blood filtration. Damage to the kidneys can be detected from albumin levels in urine, higher levels of albumin in urine indicate the kidney's filtration function is impaired. The latest breakthrough in the medical field is the use of localized sensor plasma resonance (LSPR) in the field of biosensors to detect albumin protein in urine. Using Finite-Difference Time-Domain (FDTD) simulation, the lateral size of hexagonal gold nanoparticles (AuNPs) is varied to increase the optimal LSPR. AuNPs are well-known as the most promising material for plasmonic applications. In several studies, the hexagonal geometry was reported to increase the surface area of nanoparticles as well as enhance the LSPR signal. Varying the geometry of the hexagonal AuNPs will affect their sensitivity and optical properties. In this study, the lateral size of the hexagonal AuNPs varied from 10 nm to 60 nm, with a controlled thickness of 30 nm. The absorption graph blue shifts with the peak decreasing until the graph has almost no peak as the lateral size decreases. The lateral size of 40 nm at a thickness of 30 nm was found to have the highest shifting response towards the change of refractive index, indicating good sensitivity for sensors. Simulation of hexagonal AuNPs-based LSPR detection of albumin concentrations of 0.35 –5.71 mM produces a sensitivity of 2.59 nm/mM, equivalent to 245.96 nm/RIU. The competitive performance and ease of detection procedures in real applications show the potential of the hexagonal AuNPs-based LSPR sensor to be further explored in developing alternative albumin detection techniques.

关键词： Nanoparticles Geometry Gold Sensitivity Filtration Absorption Refractive index

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Adaptive Fuzzy Sliding Mode Control With Logarithmic Sliding Surface for Active Suspension Systems

Adaptive Fuzzy Sliding Mode Control With Logarithmic Sliding...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Andika Aji Wijaya Fitri Yakub Winda Astuti Mahmud Iwan Solihin S. Syafiie Department of Mechanical Engineering University of Business and Technology (UBT) Jeddah Saudi Arabia Department of Electronic Systems Engineering University of Technology Malaysia (UTM) Kuala Lumpur Malaysia Department of Computer Engineering BINUS ASO School of Engineering Automotive and Robotics Program Bina Nusantara University (BINUS) Jakarta Indonesia Department of Mechanical and Mechatronics Engineering UCSI University Kuala Lumpur Malaysia Department of Chemical and Materials Engineering Faculty of Engineering-Rabigh King Abdulaziz University Jeddah Saudi Arabia

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

This paper introduces a hybrid control strategy that integrates the unique features of natural logarithm sliding mode control (lnSMC) and fuzzy logic systems. The lnSMC control approach ensures that the vibration amplitude remains within a bound, as determined by the parameters of the lnSMC switching function. Furthermore, the fuzzy logic system is employed to approximate the nonlinearities and uncertainties inherent in the suspension system components, such as the spring and damper. The stability of the closed-loop system is analyzed using the Lyapunov stability theorem, guaranteeing convergence within a finite time. To validate the effectiveness of the proposed controller, a simulation study was carried out using a quarter-car suspension model, considering the system’s nonlinearities, parameter uncertainties, and various external disturbances. The results indicate that the proposed controller significantly improves ride comfort while maintaining suspension deflection and road holding within critical safety limits.

关键词： Fuzzy logic Vibrations Uncertain systems Uncertainty Roads Switches Stability analysis Vehicle dynamics Springs Sliding mode control

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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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Comparative Study on Fall Detection using Machine Learning Approaches 19

Comparative Study on Fall Detection using Machine Learning A...

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19th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2022

作者： Tongskulroongruang, Thienrawit Wiphunawat, Paphatchaya Jutharee, Wisanu Kaewmahanin, Watchara Rassameecharoenchai, Teerameth Jennawasin, Tanagorn Kaewkamnerdpong, Boonserm King Mongkut's University of Technology Thonburi Department of Control Systems and Instrumentation Engineering Bangkok Thailand Institute of Field Robotics and Automation King Mongkut's University of Technology Thonburi Bangkok Thailand Naresuan University Faculty of Allied Health Sciences Department of Cardiothoracic Technology Phitsanulok Thailand King Mongkut's University of Technology Thonburi Biological Engineering Program Faculty of Engineering Bangkok Thailand

ISBN: (纸本)9781665485845

Falls are one of the most dangerous problems for the elderly. A reliable fall detection system can aid in reducing the harmful repercussions of an unintentional fall. The focus of this paper is on a dataset that includes signals from portable devices. We propose a simple feature selection approach to reduce the number of effective input attributes based on a voting strategy. The dataset is classified into three categories, i.e., pre-fall, fall and post-fall using various machine learning approaches. The computational time is significantly reduced for most of the classification algorithms, and the relative reduction reaches to 66.67% with decision tree algorithm. Classification accuracy can reach as high as 95.17% when using neural network, while the relative reductions on the classification accuracy due to the feature selection do not exceed 1.50%. © 2022 IEEE.

关键词： Decision trees

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Automatic Facial Asymmetry Analysis for Elderly Stroke Detection by using Cosine Similarity 19

Automatic Facial Asymmetry Analysis for Elderly Stroke Detec...

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19th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2022

作者： Kaewmahanin, Watchara Rassameecharoenchai, Teerameth Jutharee, Wisanu Tongskulroongruang, Thienrawit Wiphunawat, Paphatchaya Jennawasin, Tanagorn Kaewkamnerdpong, Boonserm Naresuan University Faculty of Allied Health Sciences Department of Cardiothoracic Technology Phitsanulok Thailand King Mongkut's University of Technology Thonburi Institute of Field Robotics and Automation Bangkok Thailand Mongkut's University of Technology Thonburi Department of Control Systems and Instrumentation Engineering Bangkok Thailand King Mongkut's University of Technology Thonburi Biological Engineering Program Faculty of Engineering Bangkok Thailand

ISBN: (纸本)9781665485845

For acute stroke patients, time to recognize the stroke symptom onset is crucial for the lifesaving treatment. The automatic detection of stroke signs has been increasingly developed for practical use. The better timely classification results could allow better detection of the symptoms and avoid morbidity and mortality. In this study, we proposed using cosine similarity between the left and right sides of the face as a part of features for classifying the stroke elderly patients from healthy elderly participants. We employed our method on images from the Toronto NeuroFace dataset. The results showed high classification accuracy (the average accuracy of 97.8998% from 6 classification methods). These results indicate that the cosine similarity features can be useful to detect facial asymmetry and pose very promising potential for elderly stroke detection. © 2022 IEEE.

关键词： Patient treatment

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AV Navigation in 3D Urban Environments with Curriculum-based Deep Reinforcement Learning

AV Navigation in 3D Urban Environments with Curriculum-based...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Kevin Braathen de Carvalho Iure Rosa L. de Oliveira Alexandre S. Brandão Department of Electrical Engineering Graduate Program in Computer Science Nucleus of Specialization in Robotics Universidade Federal de Viçosa Viçosa MG Brazil Department of Electrical Engineering Federal University of Viçosa Viçosa MG Brazil

Unmanned Aerial Vehicles (UAVs) are widely used in various applications, from inspection and surveillance to transportation and delivery. Navigating UAVs in complex 3D environments is a challenging task that requires robust and efficient decision-making algorithms. This paper presents a novel approach to UAV navigation in 3D environments using a Curriculum-based Deep Reinforcement Learning (DRL) approach. The proposed method utilizes a deep neural network to model the UAV’s decision-making process and to learn a mapping from the state space to the action space. The learning process is guided by a reinforcement signal that reflects the performance of the UAV in terms of reaching its target while avoiding obstacles and with energy efficiency. Simulation results show that the proposed method has a positive trade off when compared to the baseline algorithm. The proposed method was able to perform well in environments with a state space size of 22 millions, allowing the usage in big environments or in maps with high resolution. The results demonstrate the potential of DRL for enabling UAVs to operate effectively in complex environments.

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Soft Sensing Brace for Monitoring Knee Joint Kinetics and Kinematics During Squatting

Soft Sensing Brace for Monitoring Knee Joint Kinetics and Ki...

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International Conference on Ubiquitous Robots (UR)

作者： Junhwan Choi Eunseok Song Hyunkyu Park Kyoungchul Kong Jung Kim Department of Mechanical Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Robotics Program Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea

Exoskeletons have been developed to increase joint performance by providing assistance torque. Soft exosuits, which use light and soft materials for human-robot interaction, are a growing trend in the orthosis. However, wearable motion capture technology for biomechanical data collection remains a challenge. Traditional measurement systems such as motion capture camera (Mocap), inertial measurement units (IMUs), and ground reaction force and moment (GRF&M) are computationally intensive and collected in restricted laboratory environments. To address this challenge, we propose a sensing brace to monitor knee joint kinetics using an elastic strain sensor and a pressure-based mechanomyography (pMMG) sensor. The pMMG sensor improves comfort, reliability, linearity, and durability, and does not need to attach directly to the skin. Linear regression model of knee angle and moment are conducted with high reliability which showed $p-value < 0.05$ and $R^{2}$ is over 0.98. We used a linear regression model to estimate knee angle and torque during squatting with $\text{RMSE} =4.4\ deg$ in knee angle estimation and $\text{RMSE}=3.4\ Nmm/kg$ in knee moment estimation.

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Mechatronics Design of Wheeled Mobile Robotic System for Gutter Maintenance

Mechatronics Design of Wheeled Mobile Robotic System for Gut...

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IEEE International Congress on Electronics, Electrical engineering and Computing (INTERCON)

作者： Mario Arbulu Geyni Arias Brayan Iñiguez Sofia Dussan Ricardo Barreto José Cornejo Mechatronics Engineering Program CORHUILA Colombia Industrial Engineering Program CORHUILA Colombia R&D Department Robotics 4.0 Colombia Center for Space Emerging Technologies Universidad Nacional de Ingeniería Lima Peru Universidad Tecnológica del Perú Lima Peru

This paper deals with the challenges involved on roof building gutter maintenance robot design, from the problem statement of secure teleoperated semiautonomous navigation on confined gutter spaces, and the best selection of right mechatronics brush to remove the waste on gutter surface; Two concept design have been tested: Passive Brush with Parallel locomotion (PBP), and Active Brush Axial (ABA). The results on our development are shown, as following: secure robot lifting regulation, simulation environment, HMI to teleoperate, mechatronics design. Finally, some tests on simulations and current prototypes are shown, to validate our proposal, and the conclusion that the ABA design allows to remove until 85% gutter waste, instead of PBP design; furthermore, the ABA allows independent brush rotation velocity, instead of PBP design.

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A Slices Perspective for Incremental Nonparametric Inference in High Dimensional State Spaces

A Slices Perspective for Incremental Nonparametric Inference...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Moshe Shienman Ohad Levy-Or Michael Kaess Vadim Indelman Technion Autonomous Systems Program (TASP) Technion - Israel Institute of Technology Haifa Israel Robotics Institute Carnegie Mellon University Pittsburgh PA USA Department of Aerospace Engineering Technion - Israel Institute of Technology Haifa Israel

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

We introduce an innovative method for incremental nonparametric probabilistic inference in high-dimensional state spaces. Our approach leverages slices from highdimensional surfaces to efficiently approximate posterior distributions of any shape. Unlike many existing graph-based methods, our slices perspective eliminates the need for additional intermediate reconstructions, maintaining a more accurate representation of posterior distributions. Additionally, we propose a novel heuristic to balance between accuracy and efficiency, enabling real-time operation in nonparametric scenarios. In empirical evaluations on synthetic and real-world datasets, our slices approach consistently outperforms other state-of-the-art methods. It demonstrates superior accuracy and achieves a significant reduction in computational complexity, often by an order of magnitude.

关键词： Surface reconstruction Accuracy Shape Probabilistic logic Real-time systems Iterative methods Computational complexity Intelligent robots

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