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Inpatient Monitoring System: Temperature, Oxygen Saturation, Blood Pressure, Heart Rate, and Infusion Automation Based on ESP 32, IoT, and Mobile Application

Inpatient Monitoring System: Temperature, Oxygen Saturation,...

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International Conference of Computer and Informatics Engineering (IC2IE)

作者： Irvanda Joseph Patrick Anthony Winda Astuti Zener Sukra Lie Mahmud Iwan Solihin Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Department of Mechanical & Mechatronics Engineering UCSI University Kuala Lumpur Malaysia

ISBN: (数字)9798331505530

ISBN: (纸本)9798331505547

The implementation of a patient monitoring system and infusion automation which aims to ensure regular and periodic monitoring of inpatient conditions are applied in this system. This embedded system is applied in hospitals and addresses the uneven distribution of healthcare workers in Indonesia, particularly in remote areas. Currently, manual checks by nurses can lead to errors and reduced patient comfort. The improvement supervision is developed in this work. The system monitored body temperature, oxygen saturation, blood pressure, heart rate, and automated infusions. All the embedded systems are connected to Internet of Things (IoT) and a real-time database accessible through an application and web. This system allows doctors and hospital authorities to make decisions based on patient condition history. The testing phase of the system shows four data acquisition devices (temperature, oxygen saturation, blood pressure, and heart rate), an ESP 32, and Firebase as a database, have ability to capture and send real-time data every five seconds and can be accessed by doctors, patients, and hospital authorities.

关键词： Heart rate Temperature sensors Temperature measurement Automation Hospitals Databases Blood pressure Real-time systems Biomedical monitoring Testing

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HAGrasp: Hybrid Action Grasp Control in Cluttered Scenes using Deep Reinforcement Learning

HAGrasp: Hybrid Action Grasp Control in Cluttered Scenes usi...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Kai-Tai Song Hsiang-Hsi Chen Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Graduate Degree Program of Robotics National Yang Ming Chiao Tung University Hsinchu Taiwan

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Robotic autonomous grasp requires the system to perform multiple functions such as gripper and robot control, making it a task with hybrid output nature. Existing methods based on closed-loop deep reinforcement learning rely on external models for termination evaluation. To achieve more effective grasp for novel objects, we propose a new autonomous grasp control scheme termed HAGrasp that considers the complete point cloud of the workspace. It integrates grasp pose estimation, end-effector pose evaluation, and motion planning of the robotic arm into a single model, enhancing the success rate while reducing computational load. We present a closed-loop grasp control system based on deep reinforcement learning. This control system can perform grasp tasks while dynamically adjusting to avoid end-effector collisions. The design of hybrid-action reinforcement learning module is trained with unified latent action space and further improve generalization, achieving real-time autonomous grasp control. Real robot experiments show that our method has 74.2% success rate for grasping 7 unseen objects. Comparative experiments show that the proposed HAGrasp outperforms open-loop baseline Contact-Graspnet in both success rate and inference time. It is demonstrated that with integrated multi-view input and sim-to-real training design, our method improves real-world applications of autonomous grasp.

关键词： Training Point cloud compression Robot control Pose estimation Deep reinforcement learning End effectors Real-time systems

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Automatic Heliostat Directing System Based On Microcontroller ESP32

Automatic Heliostat Directing System Based On Microcontrolle...

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International Conference on Electrical Engineering and Informatics, ICEEI

作者： Richard Medyanto Nicholas Sanjaya Suryadiputra Liawatimena Computer Engineering Department Automotive & Robotics Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta

Solar energy is one of the most abundant sources of renewable energy in Indonesia. Solar energy is now typically harnessed using solar panels, but the low efficiency of photovoltaic cells requires the development of other alternatives. The heliostat is a sunlight directing device with mirrors that can be used in a concentrated solar power system. Current heliostats require high capital investment due to their large frames and expensive components. This research was undertaken to develop a lower cost heliostat using a smaller frame, ESP32 microcontroller, servo motor and low-cost components. The position of the sun can be determined using an algorithm based on the National Oceanic and Atmospheric Administration (NOAA) solar calculator, and the mirror is moved to maintain the sun's reflection on a target. The result of this research is a set of heliostat prototypes consisting of the frame and control system. Tests were carried out to test the performance of the designed heliostat and it was found that the heliostat has an accuracy of about 60 cm and can raise temperatures up to 3.41°C. The conclusion is that the heliostat can be used in a concentrated solar power system to heat boilers in solar power towers.

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Neural Network Model of Continuum Soft Robots Based on WaveNets Equipped with Adaptive IIR

Neural Network Model of Continuum Soft Robots Based on WaveN...

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International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)

作者： Oscar Federico Garcia-Castro Luis Enrique Ramos-Velasco Vicente Parra-Vega Rodolfo Garcia-Rodriguez Carlos Ernesto Vazquez-Garcia Robotics and Advanced Manufacturing CINVESTAV-IPN Ramos Arizpe Coahuila Mexico Posgraduate Program of Aeroespace Engineering Universidad Politecnica Metropolitana de Hidalgo Mexico Robotics and Advanced Manufacturing CINVESTAV-IPN Coahuila Mexico Facultad de Ciencias de la Administración Universidad Autónoma de Coahuila de Coahuila Mexico

ISBN: (数字)9798350377545

ISBN: (纸本)9798350377552

Soft robots have attracted attention from many areas, such as robotics, materials, automatic control, and artificial intelligence. The particular class of continuum soft robot (cSR) is the most challenging given its highly nonlinear dynamics from the hyperviscoelasticity and varying stiffness, which arise from the modeling of an infinite conglomerate of particles enclosed in a deformable finite-dimensional body based on the lumped parameters assumption and the D’ Alambert principle. The cSR is a complex model that presents a significant challenge in the field. Its nonintuitive structure, variable natural frequency, and parametric uncertainties, including its input matrix and lack of reliable velocity measurements, make it difficult to approximate its dynamics using only input and partial output data. This paper proposes a wavelet-based neural network (WaveNet) with an adaptive infinite impulse response (IIR) output filter. The WaveNet sweeps over modal frequencies, while the IIR enforces feedback and forward loops to propagate current and past neural outputs. The input shapes a controllable canonical output form. Simulations for a 2-degree-of-freedom CSR show that a bounded approximate modeling error is guaranteed at a low computational cost.

关键词： Backpropagation Adaptation models Time-frequency analysis Adaptive systems Uncertainty Computational modeling Neural networks Soft robotics Velocity measurement Tuning

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Continuous Adversarial Text Representation Learning for Affective Recognition

Continuous Adversarial Text Representation Learning for Affe...

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International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Seungah Son Andres Saurez Dongsoo Har CCS Graduate School of Mobility Korea Advanced Institute of Science and Technology (KAIST) Daejeon Rep. of Korea Robotics Program Korea Advanced Institute of Science and Technology (KAIST) Daejeon Rep. of Korea

ISBN: (数字)9798331507022

ISBN: (纸本)9798331507039

While pre-trained language models excel at semantic understanding, they often struggle to capture nuanced affective information critical for affective recognition tasks. To address these limitations, we propose a novel framework for enhancing emotion-aware embeddings in transformer-based models. Our approach introduces a continuous valence-arousal labeling system to guide contrastive learning, which captures subtle and multi-dimensional emotional nuances more effectively. Furthermore, we employ a dynamic token perturbation mechanism, using gradient-based saliency to focus on sentiment-relevant tokens, improving model sensitivity to emotional cues. The experimental results demonstrate that the proposed framework outperforms existing methods, achieving up to 15.5% improvement in the emotion classification benchmark, highlighting the importance of employing continuous labels. This improvement demonstrates that the proposed framework is effective in affective representation learning and enables precise and contextually relevant emotional understanding.

关键词： Representation learning Affective computing Sentiment analysis Sensitivity Text recognition Perturbation methods Semantics Contrastive learning Benchmark testing Transformers

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Renderable Street View Map-Based Localization: Leveraging 3D Gaussian Splatting for Street-Level Positioning

Renderable Street View Map-Based Localization: Leveraging 3D...

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

作者： Howoong Jun Hyeonwoo Yu Songhwai Oh Artificial Intelligence (IPAI) Seoul National University and Automation and Systems Research Institute (ASRI) and Sequor Robotics Inc. Seoul Korea Republic of Department of Intelligent Robotics & Mechanical Engineering Sungkyunkwan University (SKKU) Suwon-si Korea Republic of Department of Electrical and Computer Engineering (ECE) & Interdisciplinary Program in Artificial Intelligence (IPAI) Seoul National University and Automation and Systems Research Institute (ASRI) and Sequor Robotics Inc. Seoul Korea Republic of

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, we introduce a new method that first utilizes 3D Gaussian splatting in street-level localization problem. Robust localization with street-level real-world images such as street view is a major issue for autonomous vehicle, augmented reality (AR) navigation, and outdoor mobile robots. The objective is to determine the position and orientation of a query image that matches a street view database composed of RGB images. However, given the limited information available in the street view images, accurately determining the location solely based on this data presents a significant challenge. To address this challenge, we propose a novel method called renderable street view map-based localization (RSM-Loc). This approach enhances the localization process by augmenting 2D street view images into a renderable 3D map using 3D Gaussian splatting, to resolve street-level localization problems. Upon receiving a query RGB image without geometry information, the proposed method renders 2D images from a pre-made renderable map and compares image pose similarities between the rendered images and the query image. Through iterations of this process, the proposed method eventually estimates the pose of the given query image. The experimental results demonstrate that RSM-Loc outperforms the baselines with neural-field-based localization. Additionally, we conduct deep analysis on the proposed method to show that our method can serve as a new concept for the street-level localization problem.

关键词： Location awareness Visualization Matched filters Three-dimensional displays Image resolution Navigation Noise measurement Mobile robots Intelligent robots Image reconstruction

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How Fast Can a Robotic Drummer Beat Using Dielectric Elastomer Actuators?

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IEEE robotics and Automation Letters 2024年第3期9卷 2638-2645页

作者： Wakle, Sudhir Lin, Tse-Han Huang, Shu Basu, Sumit Lau, Gih-Keong National Yang Ming Chiao Tung University International College of Semiconductor Technology Hsinchu30010 Taiwan Indian Institute of Technology Kanpur Mechanical Engineering Department Kanpur208016 India National Yang Ming Chiao Tung University Department of Graduate Degree Program of Robotics Hsinchu30010 Taiwan Industrial Technology Research Institute Mechanical and Mechatronics System Research Labs Zhudong 31057 Taiwan National Yang Ming Chiao Tung University Department of Mechanical Engineering International College of Semiconductor Technology Hsinchu30010 Taiwan

Fast drumming presents a speed challenge to many robotic arms. To simultaneously meet the needs for speed, stroke, and force, we proposed and tested a new double-saddle dielectric elastomer actuator (DEA) as the artificial biceps for driving a lightweight robotic drummer. This work finds that fast force induction is instrumental to the fast drumming by a DEA-driven drumstick. While a pure-shear series of DEA under a large pre-stretch and lateral reinforcement can generate a large isotonic stroke, it is not fast in isometric force induction. Instead, this work found a double-saddle DEA, which is a degenerated two-segment pure-shear DEA with a middle laterally buckled beam, managed to induce a faster isometric force at a 0.5 s down time constant when its ultimate actuation tapered due to substantial strain stiffening effect. As such, this double-saddle DEA-driven drummer suffered less from the dynamic stroke decrement than the 8-segment DEA did. A 4.4 g DEA managed to swing freely a 7.8 g drumstick up to nearly 60° at 6 kV and a maximum tip speed of up to 0.45 m/s. The drumming frequency upon 5.5 kV activation was up to 2-2.5 Hz. In comparison, an 8-segment pure-shear DEA-driven drummer failed to reach the drum when pulsed at 2 Hz. Interestingly, a slower stroke excited multiple drumbeats due to secondary bounces. To achieve a faster drumming to match a human drummer, it is foreseen that a harder dielectric elastomer material will help drive a faster soft robot. © 2016 IEEE.

关键词： Dielectric materials

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In-hand manipulation of a circular dynamic object by soft fingertips without angle measurement

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Science China(Information Sciences) 2021年第5期64卷 193-208页

作者： R.GARCIA-RODRIGUEZ V.PARRA-VEGA Aeronautical Engineering Program and Postgraduate Program in Aerospacial Engineering Universidad Politecnica Metropolitana de Hidalgo Robotics and Advanced Manufacturing Department Research Center for Advanced Studies (CINVESTAV)

A multi-fingered robotic hand with curved fingertips enables contact re-positioning without reattaching at the expense of fingertip rolling. This rolling stands for a characteristic that facilitates dexterous manipulation but results in an algebraically complex dynamic model subject to such constraints. The hemispherical shape of fingertips allows a dexterous manipulation when controlling the tangent forces, which are essential to rotate object. However, the measurement of the object angle in practice requires tactile-optical sensing. In this paper, considering robotic fingers with curved soft tips, we propose a feedback control that ensures optimal dynamical grasping of a circular rigid object. It is shown that the collaboration of the contact forces, to get a minimum pose of internal forces, and the tangential forces, to induce the conditions for assuring the grasp closure, is necessary to get a skillful manipulation. In this case, the orientation control of a circular object to the desired angle while avoiding direct measurement of the object angle is presented. Stability conditions of the system are presented in the sense of stability-in-the-manifold. Finally, representative simulations are shown and discussed.

关键词： optimal grasping manipulation soft-fingertips circular object stability-in-the-manifold

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A Real-time Affordance-based Object Pose Estimation Approach for Robotic Grasp Pose Estimation

A Real-time Affordance-based Object Pose Estimation Approach...

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International Conference on System Science and Engineering (ICSSE)

作者： Shang-Wen Wong Yu-Chen Chiu Chi-Yi Tsai Doctoral Program in Robotics College of Engineering Tamkang University New Taipei City Taiwan Department of Electrical and Computer Engineering Tamkang University New Taipei City Taiwan

This paper proposes a pose estimation system for robot grasping based on a novel Object Affordance Detection and Segmentation (OADS) network. The proposed system consists of four modules: (1) OADS network; (2) point cloud extraction; (3) object pose estimation; (4) grasp pose estimation. Based on the OADS network, the proposed system achieves affordance-based object pose estimation results. The proposed grasp pose estimation system is evaluated on a laboratory-made dual-arm robot. Experimental results show that the proposed system achieves high detection rate and high accuracy in affordance detection and segmentation tasks, leading to a high success rate in object grasping tasks with lab-made dual-arm robot.

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Ant Colony Optimization Algorithm Enhancement for Better Performance

Ant Colony Optimization Algorithm Enhancement for Better Per...

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AI IoT Congress (AIIoT), World

作者： Mohammed Faisal Fahad Albogamy Center of AI & Robotics (CAIR) Kuwait College of Science and Technology (KCST) Kuwait Computer Sciences Program Turabah University College Taif University Taif Saudi Arabia

The scientific field of swarm intelligence is related to swarms existing in natural systems. Numerous systems and Algorithms built on swarm intelligence have appeared addressing optimization problems, including: Firefly Algorithm (FA), Ant System (AS), Particle Swarm Optimization (PSO), Intelligent Water Drops (IWD), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), and many others. The foraging behavior of the ant’s system inspired the researchers to generate the ACO and use it to solve optimization problems. In this research, we introduce the ACOStar algorithm to improve the performance of ACO by including the evaluation function of A* algorithm on the transition-probability function of ACO. To demonstrate the success of the proposed algorithm, we applied the suggested algorithm to the shortest path problem. All experiments demonstrate the success and the accuracy of the proposed algorithm.

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