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IEEE International Conference on Soft robotics (RoboSoft)

作者： Christina Chase-Markopoulou Anoush Sepehri Tania K. Morimoto Michael T. Tolley Department of Mechanical and Aerospace Engineering Department of Surgery Materials Science and Engineering Program University of California San Diego CA USA

ISBN: (数字)9798331520205

ISBN: (纸本)9798331520212

Many wearable soft robotic devices have been developed to assist with spasticity – the increased muscle tone seen in individuals with neurological conditions such as stroke or cerebral palsy. However, these devices typically lack the ability to individually assist multiple degrees of freedom (DOF), which is essential to performing a broad range of daily tasks. To address this need, we developed a soft robotic thumb orthosis to achieve movement in three DOF. We focused on the thumb as it performs the most complex movement. Our orthosis used three unfolding textile pneumatic actuators to assist with the extension of the interphalangeal joint, combined extension of the metacarpal and carpometacarpal joints, and abduction of the carpometacarpal joint. The orthosis was tested on both a 3D-printed biomimetic test bed that emulated spasticity and a healthy individual. The orthosis met the full range of motion targets for each joint, except for the abduction of the carpometacarpal joint with medium spasticity, and surpassed the range of motion threshold required for activities of daily living. The orthosis was able to: (1) assist each DOF independently, (2) move the tip of a biomimetic thumb to a pre-determined target with total error of less than 1.5 cm when actuated with open-loop control, and, (3) provide individual joint assistance to a user with no motor impairment. This research showcases the ability of a soft robotic orthosis to assist movement in simulated spasticity of individual thumb joints and provides an important step towards a platform to study whether independent joint assistance during rehabilitation improves patient outcomes.

关键词： Performance evaluation Pneumatic actuators Biomimetics Thumb Spasticity Soft robotics Muscles Motors Motion control Textiles

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Addressing Biases in Gastric Cancer Diagnosis Through Generative Models and Vision-Based Surface Tactile Sensing

Addressing Biases in Gastric Cancer Diagnosis Through Genera...

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Medical Imaging 2025: Image-Guided Procedures, Robotic Interventions, and Modeling

作者： Kapuria, Siddhartha Ikoma, Naruhiko Chinchali, Sandeep Alambeigi, Farshid Walker Department of Mechanical Engineering and The Texas Robotics The University of Texas at Austin Austin TX United States Texas Robotics The University of Texas at Austin Austin TX United States Department of Surgical Oncology Division of Surgery The University of Texas MD Anderson Cancer Center Houston TX United States Chandra Family Department of Electrical and Computer Engineering and The Texas Robotics The University of Texas at Austin Austin TX United States

ISBN: (纸本)9781510685949

Towards developing an informed, intuitive, and generalized artificial intelligence model for endoscopic diagnosis of Advanced Gastric Cancer (AGC) lesions, in this work, we extend the use of generative models to augment limited and biased training datasets. This approach aims to enhance model performance and generalizability, tackling the challenge of acquiring sizable and well-balanced datasets in the clinical domain. We applied this approach to our unique dataset comprised of textural images of additively-manufactured realistic AGC tumor phantoms collected using a robotic data collection system and our unique Vision-based Tactile Sensor - HySenSe. Our approach was particularly suited to this dataset, since HySenSe's limited sensing area captures only partial images of the much larger AGC lesions, which reduces the amount of information available in a single image. We trained a single Class-Conditioned Latent Diffusion Model (CC-LDM) on an artificially imbalanced dataset of HySenSe images, logging performance using Fréchet Inception Distance (FID), and exploring different hyperparameter configurations. Using the high-quality synthetic images generated using this model, we performed experiments using our previously developed Dilated ResNet model for AGC tumor classification with the following objectives: (i) study the amount of synthetic data required during training, and (ii) compare different data addition strategies during model training using cross-validation. Note that while the models were trained using both real and synthetic textural images, testing was performed solely on real images. Our experiments showed that the trained classifier demonstrates improved generalizability when trained on a mixture of real and synthetic images, but not all methods of mixing the data are equally effective. Overall, the model shows improved performance even under mixed morphological tumor conditions and partial sensor contact. © 2025 SPIE

关键词： gastric cancer diagnosis generative models machine learning Vision-based tactile sensing

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Untethered Micro/Nanorobots for Remote Sensing:Toward Intelligent Platform

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Nano-Micro Letters 2024年第2期16卷 450-483页

作者： Qianqian Wang Shihao Yang Li Zhang Jiangsu Key Laboratory for Design and Manufacture of Micro‑Nano Biomedical Instruments School of Mechanical EngineeringSoutheast UniversityNanjing 211189People’s Republic of China Department of Mechanical and Automation Engineering The Chinese University of Hong KongShatinHong Kong 999077People’s Republic of China Chow Yuk Ho Technology Centre for Innovative Medicine The Chinese University of Hong KongShatinHong Kong 999077People’s Republic of China T Stone Robotics Institute The Chinese University of Hong KongShatinHong Kong 999077People’s Republic of China Department of Surgery The Chinese University of Hong KongShatinHong Kong 999077People’s Republic of China

Untethered micro/nanorobots that can wirelessly control their motion and deformation state have gained enormous interest in remote sensing applications due to their unique motion characteristics in various media and diverse *** are developing micro/nanorobots as innovative tools to improve sensing performance and miniaturize sensing systems,enabling in situ detection of substances that traditional sensing methods struggle to *** the past decade of development,significant research progress has been made in designing sensing strategies based on micro/nanorobots,employing various coordinated control and sensing *** review summarizes the latest developments on micro/nanorobots for remote sensing applications by utilizing the self-generated signals of the robots,robot behavior,microrobotic manipulation,and robot-environment *** recent studies and relevant applications in remote sensing,we also discuss the challenges and future perspectives facing micro/nanorobots-based intelligent sensing platforms to achieve sensing in complex environments,translating lab research achievements into widespread real applications.

关键词： Micro/nanorobot Remote sensing Wireless control Self-propulsion Actuation at small scales

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ExSLeR: Development of a Robotic Arm for Human Skill Learning

ExSLeR: Development of a Robotic Arm for Human Skill Learnin...

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

作者： Deokjin Lee Kiyoung Choi Junyoung Kim Wonbum Yun Taehoon Kim Kanghyun Nam Sehoon Oh Department of Robotics and Mechatronics Engineering DGIST Daegu Korea Department of Mechanical Engineering Yeungnam University Gyeongsan Korea

The trend in robotics has shifted from collaboration with humans to learning and reproducing human skills, reflecting a growing social demand. In response, it is imperative to consider both hardware and software aspects in the design of robots. On the hardware side, the robot should be equipped with adequate sensors for mimicking human motion and force, and its design should meet necessary requirements such as workspace, degree of freedom, payload capacity, and weight, all of which are contingent upon the intended use of the robot. On the software side, the robot should be equipped with a real-time system and stable control algorithms to ensure safe operation. This paper presents the ExSLeR arm which meets the requirements for human skill learning. The performance of the ExSLeR arm is validated by a set of experiments through motion tracking with heavy payload and compliant interaction control tasks.

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Automated classification of big X-ray diffraction data using deep learning models

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npj Computational Materials 2023年第1期9卷 169-180页

作者： Jerardo E.Salgado Samuel Lerman Zhaotong Du Chenliang Xu Niaz Abdolrahim Materials Science program University of RochesterRochesterNew York 14627USA Department of Computer Science University of RochesterRochesterNew York 14627USA Department of Mechanical Engineering University of RochesterRochesterNew York 14627USA Laboratory for Laser Energetics University of RochesterRochesterNew York 14627USA

In current in situ X-ray diffraction(XRD)techniques,data generation surpasses human analytical capabilities,potentially leading to the loss of *** techniques require human intervention,and lack the performance and adaptability required for material *** the critical need for high-throughput automated XRD pattern analysis,we present a generalized deep learning model to classify a diverse set of materials’crystal systems and space *** our approach,we generate training data with a holistic representation of patterns that emerge from varying experimental conditions and crystal *** also employ an expedited learning technique to refine our model’s expertise to experimental *** addition,we optimize model architecture to elicit classification based on Bragg’s Law and use evaluation data to interpret our model’s *** evaluate our models using experimental data,materials unseen in training,and altered cubic crystals,where we observe state-of-the-art performance and even greater advances in space group classification.

关键词： Automate classify cubic

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The compressive properties of AZ92A magnesium alloy containing titanium were studied by varying the hot-pressing and annealing temperature ranges

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Materials Today: Proceedings 2022年 59卷 1491-1497页

作者： Ravi Raj, V. Jagadeesha, S. Pradeep Kumar, K.V. Shara Shata, Agegnehu Sathish Kumar, P. Madhavarao, S. Puthilibai, G. Department of Mechanical Engineering Sri Sairam Engineering College Tamil Nadu Chennai600044 India Department of Mathematics Nitte Meenakshi Institute of Technology Karnataka Bengaluru560064 India Department of Mechanical Engineering M S Ramaiah Institute of Technology Karnataka Bengaluru560054 India Faculty of Mechanical Engineering Arba Minch Institute of Technology Arba Minch University Arba Minch Ethiopia Department of Robotics & Automation United Institute of Technology G.Koundampalayam Tamil Nadu Coimbatore641020 India Andhra Pradesh Bhimavaram534204 India Department of Chemistry Sri Sairam Engineering College Sai Leo Nagar West Tambaram Tamilnadu Chennai600044 India

Extremely high strength can only be achieved through the use of magnesium alloys devoid of rare earth elements, as well as the development of a microstructure for a nanocrystalline matrix and the dispersion of stable nanoscale precipitates. This study used mechanical milling and hot pressing to create a bulk nanocrystalline magnesium alloy. The structure, densification, and mechanical characteristics of hot pressed samples were studied. The magnesium matrix had an average grain size of 76 nm after hot pressing at 723 K for 60 min. Particles as small as 10 nm in diameter of nanoscale Ti3Al precipitates were discovered. It was then subjected to various annealing treatments at 573 K. The material's tensile and plastic properties both improved noticeably. After 80 h of annealing at 573 K, its yield strength, compressive strength, strain, and stiffness were all greater than 498 Mpa. Grain boundary reinforcement, the Orowan outcome, and load transmission all contributed to a total of 64, 33, and 3percent of the total respectively. The use of nanocrystalline magnesium and nanoscale Ti3Al precipitates results in extremely high strength. © 2021

关键词： Magnesium alloys

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Stretchable R-G-B haptic soft optical sensor for human-robot interaction

Stretchable R-G-B haptic soft optical sensor for human-robot...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Gyohyeon Song Jiseong Shin Hugo Rodrigue Department of Intelligent Robotics Sungkyunkwan University Suwon Korea Department of Mechanical Engineering Sungkyunkwan University Suwon Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

Polymer-based optical sensors, renowned for their flexibility and stretchability, have found extensive application as displacement sensors in the soft robotics and wearable robotics. Emitting from LEDs, light traverses through a transparent and flexible polymer core, thereby modulating the intensity of light detected by photodiodes contingent upon alterations in the core's cross-sectional area induced by sensor deformation. Due to its polymer composition, it offers flexibility, enabling free deformation, while its ability to measure light intensity demonstrates immunity to external magnetic and electric fields. In this study, a novel haptic sensor was devised by integrating color filters into polymer-based optical sensors to detect specific wavelengths from the LED's initial spectrum. Pressing of Red, Green, and Blue color filters enclosing the core enables light transmission through the filters. The spectrometer detects wavelengths ranging from 415nm to 680nm through eight channels, sufficiently covering the visible spectrum. Furthermore, it was ascertained that wavelength classification by color filters remains unaffected even with a decrease in initial intensity of light due to sensor deformation. Hence, the application of this sensor in wearable robotics or soft robotics is envisaged to facilitate simultaneous displacement measurement and haptic feedback, enhancing control and measurement capabilities.

关键词： Filters Deformation Magnetic cores Wavelength measurement Soft robotics Robot sensing systems Sensors Haptic interfaces Optical sensors Polymers

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2022 International Siberian Conference on Control and Communications, SIBCON 2022

作者： Tsoy, Tatyana Safin, Ramil Sultanov, Ramir Saha, Subir Kumar Magid, Evgeni Kazan Federal University Intelligent Robotics Department Kazan Russia Indian Institute of Technology Delhi Mechanical Engineering Department New Delhi India

ISBN: (纸本)9781665476287

Fiducial marker (FM) systems have a wide range of applications, such as augmented reality, human-robot interaction, medical surgery, robot navigation, and swarm robotics. Moreover, FMs enable to calibrate optical sensors, which is a crucial step in most computer vision algorithms. A variety of considerations should be taken into account to decide which FM system is suitable for a particular application. This paper proposes a list of recommended criteria that allow to compare FM systems. The criteria support a FM ranking according to their properties and enable users to choose a set of FMs best suited for a specific task. A number of the recommended criteria efficiency and performance were validated in the Gazebo simulation and in a real world environment using Servosila Engineer mobile robot. © 2022 IEEE.

关键词： Augmented reality

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Bioactive injectable composites based on insulin-functionalized silica particles reinforced polymeric hydrogels for potential applications in bone tissue engineering

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Journal of Materials Science & Technology 2022年第10期105卷 153-163页

作者： Aleksandra Krajcer Joanna Klara Wojciech Horak Joanna Lewandowska-Łańcucka Faculty of Chemistry Jagiellonian UniversityGronostajowa 2Kraków 30-387Poland AGH University of Science and Technology Faculty of Mechanical Engineering and RoboticsDepartment of Machine Design and TechnologyAl.Mickiewicza 30Kraków 30-059Poland

Novel bioactive injectable composites based on biopolymeric hydrogels reinforced with insulin-functionalized silica particles were *** insulin(INS)was immobilized on the surface of amine-modifed silica particles employing covalent attachment by EDC/NHS chemistry and via electrostatic *** resulting formulations were examined for the morphology(SEM),chemical composition(FTIR,XPS)as well as protein *** facilitate the injectability and support the bone regeneration,developed particles were dispersed in biopolymeric sol composed of collagen,chitosan and lysinemodifed hyaluronic acid and crosslinked with *** means of rheological study,the sol-gel in situ transition of obtained systems was *** was found in vitro study that MG-63 cells cultured on the developed composites exhibit signifcantly higher alkaline phosphatase(ALP)activity,compared to the pristine ***,the biomineralization ability in the simulated body fluid(SBF)model was also *** fndings suggest that proposed herein novel hydrogel-based composites might be the promising formulation for regeneration of bone defects,especially as a less-cost effective support/alternative for BMP-2 systems.

关键词： Injectable composites Biopolymers Insulin-functionalized silica particles Bone tissue engineering

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A Tetherless Soft Robotic Wearable Haptic Human Machine Interface for Robot Teleoperation

A Tetherless Soft Robotic Wearable Haptic Human Machine Inte...

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

作者： Shilpa Thakur Nathalia Diaz Armas Joseph Adegite Ritwik Pandey Joey Mead Pratap M. Rao Cagdas D. Onal Worcester Polytechnic Institute (WPI) Worcester MA USA Robotics Engineering Department University of Massachusetts Lowell Lowell MA USA Plastics Engineering Department Mechanical and Materials Engineering Department

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This work describes the development, demonstration, and performance evaluation study of a wearable human machine interface for robotic teleoperation. We present a novel tetherless human machine interface in the form of a backpack, wearable 3D arm motion capture sensors, finger flexion sensors, and pneumatic haptic feedback muscles. The system is integrated in a complete teleoperation framework, enabling users to be immersed in a remote environment through virtual reality headgear, facilitating intuitive manipulation of an industrial articulated arm. The human machine interface samples the kinematic configuration of the user’s arm, hand, and fingers using multiple inertial measurement units and capacitive sensors respectively, and streams it to the teleoperation software stack. The gripping forces experienced at the robot’s end-effector are acquired using a custom three-dimensional Hall-effect magnetic sensor. The system simultaneously renders the kinesthetic and tactile feedback on the user’s fingers through custom designed pneumatically actuated soft robotic haptic muscles. The efficacy of the human machine interface and the teleoperation system was tested and evaluated by conducting user studies, which showed 31.4% faster teleoperation compared to a keypad controller, and 60% less gripping force utilized with haptics enabled. The findings of the study guided the design and prototype development of a printed electronics based stretchable sleeve and glove motion capture unit to improve the portability, ergonomics, and user experience of the human machine interface.

关键词： Human-machine systems Tactile sensors Virtual reality Soft robotics Muscles Three-dimensional printing Motion capture User experience Haptic interfaces Wearable sensors

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