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Smooth Surface-to-Surface Contact Control for Rope-Base Soft-Tip Manipulator

IEEE Transactions on Automation Science and engineering 2025年 22卷 16297-16308页

作者： Guangli Sun Fangxun Zhong Peng Li Linzhu Yue Zhi Chen Xiang Li Yun-Hui Liu Department of Mechanical and Automation Engineering T Stone Robotics Institute The Chinese University of Hong Kong Shatin SAR Hong Kong School of Science and Engineering The Chinese University of Hong Kong Shenzhen China School of Mechanical Engineering and Automation Harbin Institute of Technology at Shenzhen Shenzhen China Hong Kong Centre for Logistics Robotics SAR Hong Kong Department of Automation Tsinghua University Beijing China

A new control pipeline has been proposed for the Rope-Base Soft-tip Manipulator (RBSM) to execute the surface contact task to prevent the jamming and slipping problems. The control pipeline enables smooth surface-to-surface contact for the RBSM using only force sensors, eliminating the dependence on additional pose measurement of the window surface plane and soft-tip deformation information. The pipeline consists of three steps: free contact step implemented by an exponential force shape controller to avoid force overshoot to the window surface; orientation refinement step implemented by a force and torque combined controller to make the RBSM cleaning head surface stable adapt to the smooth window surface; and finally, a release normal force step to reduce head jamming and region covering with a pre-defined vibration-less cleaning trajectory for smooth cleaning on the slippery window surface. The proposed pipeline has been validated in a Rope base Cleaning Manipulator prototype to clean a common window surface. The force and velocity curves during the cleaning experiment show that the proposed method achieves smooth scraping and cleaning under unknown initial significant errors in surface orientation. Note to Practitioners—The current robotic rope base high-rise exterior work, especially cleaning, is not efficient due to the instability of the base and the influence of the soft-tip on the window and end-effector contact. A new control pipeline has been proposed for the Rope-Base Soft-tip Manipulator (RBSM) to clean the window surface smoothly to avoid jamming, slipping, and leaving problems in the contact process. The control pipeline realizes smooth surface-to-surface contact of RBSM with only force sensors without additional pose measurement of the window surface plane. The pipeline consists of three steps: free contact step implemented by an exponential force shape controller to avoid force overshoot to the window surface; orientation refinement step implemented

关键词： Surface cleaning Force Manipulators Robots Jamming Pipelines End effectors Trajectory Surface impedance Force sensors

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Intelligent upper-limb exoskeleton integrated with soft bioelectronics and deep learning for intention-driven augmentation

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npj Flexible Electronics 2024年第1期8卷 856-868页

作者： Jinwoo Lee Kangkyu Kwon Ira Soltis Jared Matthews Yoon Jae Lee Hojoong Kim Lissette Romero Nathan Zavanelli Youngjin Kwon Shinjae Kwon Jimin Lee Yewon Na Sung Hoon Lee Ki Jun Yu Minoru Shinohara Frank L.Hammond Woon-Hong Yeo Department of Mechanical Roboticsand Energy EngineeringDongguk UniversitySeoul 04620Republic of Korea IEN Center for Wearable Intelligent Systems and Healthcare Institute for Electronics and NanotechnologyGeorgia Institute of TechnologyAtlantaGA 30332USA School of Electrical and Computer Engineering Georgia Institute of TechnologyAtlantaGA 30332USA George W.Woodruff School of Mechanical Engineering Georgia Institute of TechnologyAtlantaGA 30332USA School of Industrial Design Georgia Institute of TechnologyAtlantaGA 30332USA School of Electrical and Electronic Engineering Yonsei UniversitySeoul 03722Republic of Korea School of Biological Sciences Georgia Institute of TechnologyAtlantaGA 30332USA Wallace H.Coulter Department of Biomedical Engineering Georgia Institute of Technology and Emory University School of MedicineAtlantaGA 30332USA Institute for Materials Parker H.Petit Institute for Bioengineering and BiosciencesInstitute for Robotics and Intelligent MachinesGeorgia Institute of TechnologyAtlantaGA 30332USA

The age and stroke-associated decline in musculoskeletal strength degrades the ability to perform daily human tasks using the upper ***,we introduce an intelligent upper-limb exoskeleton system that utilizes deep learning to predict human intention for strength *** embedded soft wearable sensors provide sensory feedback by collecting real-time muscle activities,which are simultaneously computed to determine the user’s intended *** deep learning predicts four upper-limb joint motions with an average accuracy of 96.2%at a 500–550 ms response rate,suggesting that the exoskeleton operates just by human *** addition,an array of soft pneumatics assists the intended movements by providing 897 newtons of force while generating a displacement of 87mm at *** intent-driven exoskeleton can reduce human muscle activities by 3.7 times on average compared to the unassisted exoskeleton.

关键词： skeleton learning utilize

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A Framework for Modeling and Control for Extrusion-based Additive Manufacturing

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IFAC-PapersOnLine 2024年第28期58卷 138-143页

作者： Nazanin Farjam Trushant Adeshara Dawn Tilbury Kira Barton Department of Robotics University of Michigan Ann Arbor MI 48109 USA Department of Mechanical Engineering University of Michigan Ann Arbor MI 48109 USA

Additive manufacturing (AM) processes have experienced a surge in demand, largely driven by the growing need for customization across various industries. This paradigm shift underscores the need for more robust AM processes, where precise customization is vital to meet individual requirements. However, there does not exist a structured framework for deriving models that characterize the relationship between process parameters and pattern characteristics. Additionally, determining critical inputs and outputs, as well as control strategies for in situ AM control, further compounds this challenge. This work addresses these challenges by proposing a structured approach to closing the loop for an extrusion-based AM printing process, demonstrating its transferability across multiple printers within the same AM family. The control framework was tested under scenarios of nozzle clogging and over-extrusion, demonstrating effective error mitigation and rapid convergence with appropriate controller gain designs. Moreover, The framework was successfully transferred to a different extrusion printer, showing its adaptability across varied environments and printers, offering insights into the underlying dynamics of this extrusion-based AM process, and paving the way for enhanced performance and reliability in AM.

关键词： process modelling control additive manufacturing extrusion-based printing run-to-run control

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Developmental Prediction of Poststroke Patients in Activities of Daily Living by Using Tree-Structured Parzen Estimator-Optimized Stacking Ensemble Approaches

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IEEE Journal of Biomedical and Health Informatics 2024年第5期28卷 2745-2758页

作者： Lin, Pei-Hua Kuo, Ping-Huan Chen, Kuan-Lin China Medical University An Nan Hospital Tainan70965 Taiwan National Chung Cheng University Department of Mechanical Engineering Chiayi62102 Taiwan National Chung Cheng University Advanced Institute of Manufacturing with High-tech Innovations Chiayi62102 Taiwan National Pingtung University Department of Intelligent Robotics Pingtung90004 Taiwan

Poststroke injuries limit the daily activities of patients and cause considerable inconvenience. Therefore, predicting the activities of daily living (ADL) results of patients with stroke before hospital discharge can assist clinical workers in formulating more personalized and effective strategies for therapeutic intervention, and prepare hospital discharge plans that suit the patients needs. This study used the leave-one-out cross-validation procedure to evaluate the performance of the machine learning models. In addition, testing methods were used to identify the optimal weak learners, which were then combined to form a stacking model. Subsequently, a hyperparameter optimization algorithm was used to optimize the model hyperparameters. Finally, optimization algorithms were used to analyze each feature, and features of high importance were identified by limiting the number of features to be included in the machine learning models. After various features were fed into the learning models to predict the Barthel index (BI) at discharge, the results indicated that random forest (RF), adaptive boosting (AdaBoost), and multilayer perceptron (MLP) produced suitable results. The most critical prediction factor of this study was the BI at admission. Machine learning models can be used to assist clinical workers in predicting the ADL of patients with stroke at hospital discharge. © 2013 IEEE.

关键词： Forecasting

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Correction: Materials laboratories of the future for alloys, amorphous, and composite materials (MRS Bulletin, (2025), 50, 2, (190-207), 10.1557/s43577-024-00846-y)

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MRS Bulletin 2025年 1-2页

作者： Banerjee, Sarbajit Meng, Y. Shirley Minor, Andrew M. Zhang, Minghao Zaluzec, Nestor J. Chan, Maria K.Y. Seidler, Gerald McComb, David W. Agar, Joshua Mukherjee, Partha P. Melot, Brent Chapman, Karena Guiton, Beth S. Klie, Robert F. McCue, Ian D. Voyles, Paul M. Robertson, Ian Li, Ling Chi, Miaofang Destino, Joel F. Devaraj, Arun Marquis, Emmanuelle A. Segre, Carlo U. Liu, Huinan H. Yang, Judith C. Momeni, Kasra Misra, Amit Abdolrahim, Niaz Medvedeva, Julia E. Cai, Wenjun Sehirlioglu, Alp Dizbay-Onat, Melike Mehta, Apurva Graham-Brady, Lori Maruyama, Benji Rajan, Krishna Warner, Jamie H. Taheri, Mitra L. Kalinin, Sergei V. Reeja-Jayan, B. Schwarz, Udo D. Simon, Sindee L. Brown, Craig M. Department of Chemistry and Department of Materials Science & Engineering Texas A & M University College Station United States Pritzker School of Molecular Engineering The University of Chicago Chicago United States Department of Materials Science & Engineering University of California Berkeley Berkeley United States National Center for Electron Microscopy Molecular Foundry Lawrence Berkeley National Laboratory Berkeley United States Center for Nanoscale Materials Argonne National Laboratory Lemont United States Department of Physics University of Washington Seattle United States Department of Materials Science & Engineering The Ohio State University Columbus United States Department of Mechanical Engineering and Mechanics Drexel University Philadelphia United States School of Mechanical Engineering Purdue University West Lafayette United States Department of Chemistry University of Southern California Los Angeles United States Department of Chemistry Stony Brook University The State University of New York Stony Brook United States Department of Chemistry University of Kentucky Lexington United States Department of Physics University of Illinois at Chicago Chicago United States Department of Materials Science & Engineering Northwestern University Evanston Bangladesh Department of Materials Science & Engineering University of Wisconsin–Madison Madison United States Department of Materials Science and Engineering University of Pennsylvania Philadelphia United States Department of Mechanical Engineering and Materials Science Duke University Durham United States Department of Chemistry Creighton University Omaha United States Physical and Computational Sciences Directorate Pacific Northwest National Laboratory Richland United States Department of Materials Science & Engineering University of Michigan–Ann Arbor Ann Arbor United States Department of Physics Illinois Institute of Technology Chicago United States Department of Bioengineering and the Mater

This article was updated to correct Minghao Zhang’s affiliation from "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA" to "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA;Argonne National Laboratory, Lemont, USA." Argonne National Laboratory was left off the original publication. © The Author(s) 2025.

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Effect of chemical composition and microstructure on the thermal conductivity of Mg-Al-Ca alloys

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Keikinzoku/Journal of Japan Institute of Light Metals 2024年第1期74卷 9-13页

作者： Kirimoto, Yuichi Kondo, Natsuki Ito, Mizuki Tsukeda, Tadayoshi Aida, Tetsuo Tabata, Hironobu Kurihara, Hideki Suzuki, Mayumi Department of Nano and Functional Material Science Graduate School of Science and Engineering for Education University of Toyama 3190 Gofuku Toyama-shi Toyama930-8555 Japan School of Sustainable Design Materials and Engineering University of Toyama Toyama-shi Toyama Japan Program of Materials Science and Engineering Studies in Science and Engineering Graduate School of Science and Engineering University of Toyama Toyama-shi Toyama Japan Faculty of Sustainable Design Academic Assembly University of Toyama Toyama-shi Toyama Japan CHUETSU METAL WORKS CO. LTD. Nakaniikawa-gun Toyama Japan Saitama Industrial Technology Center Kawaguchi-shi Saitama Japan Department of Mechanical Systems Engineering Faculty of Engineering Toyama Prefectural University Imizu-shi Toyama Japan

In recent years, the increasing demand for electric vehicles, digital devices such as PCs and smartphones, and renewable energy storage systems has created a need for higher-performance batteries. Accordingly, the thermal conductivity of the case that houses the battery is becoming increasingly important. In this study, compositions with high thermal conductivity and good castability were investigated, focusing on Mg-Al-Ca alloys, and the relationship between the two was examined through thermal conductivity measurements and microstructural observations. As a result, the Mg-6%Al-4%Ca alloy was optimal in terms of castability and thermal conductivity. It was confirmed that a lower Al solid solution capacity and a higher purity of the matrix phase are important to improve the thermal conductivity. It is also suggested that the second phase, platelet Al2Ca, is likely to be recognized and enriched in the matrix, contributing to the improvement of thermal conductivity. The amount of Ca solid solution in the matrix was suggested to be reduced by the enrichment of Al in the matrix. The Ca solid solution in the matrix was found to be less effective in reducing thermal conductivity than the Al solid solution. © 2024 The Japan Institute of Light Metals.

关键词： Magnesium alloys

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Environmentally-friendly alkaline ionized water pretreatment and hydrolysis of macroalga via microwave-assisted heating to improve monosaccharide yield for bioethanol production

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Process Safety and Environmental Protection 2024年 189卷 702-713页

作者： Chen, Wei-Hsin Liu, Li-Xuan Khoo, Kuan Shiong Sheen, Herng-Kuang Kwon, Eilhann E. Saravanakumar, Ayyadurai Chang, Jo-Shu Department of Aeronautics and Astronautics National Cheng Kung University Tainan701 Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung411 Taiwan International Master Degree Program on Energy National Cheng Kung University Tainan701 Taiwan Department of Chemical Engineering and Materials Science Yuan Ze University Taoyuan Taiwan Sugar Business Division Taiwan Sugar Corporation Taiwan701 Taiwan Department of Earth Resources and Environmental Engineering Hanyang University Seoul04763 Korea Republic of Directorate of Research SRM Institute of Science and Technology Chengalpattu District Tamil Nadu Kattankulathur603203 India Department of Chemical Engineering and Materials Science College of Engineering Tunghai University Taichung Taiwan Department of Chemical Engineering National Cheng Kung University Tainan Taiwan

This study synthesizes three sequential steps: pretreatment, acid hydrolysis, and enzyme hydrolysis for bioethanol and hydrochar production from macroalga Gracilaria. The Taguchi method is employed separately in each step to optimize relevant operating factors, aiming to maximize the monosaccharide yield. During pretreatment, environmentally friendly alkaline ionized water is utilized as it does not contain chemical additives. Afterward, microwave-assisted hydrolysis is adopted to enhance the monosaccharide yield of the macroalga for bioenergy production. The results show that the total sugar of Gracilaria undergoing acid hydrolysis alone is 28.72 g‧L−1. The total sugar content after alkaline pretreatment followed by acid hydrolysis is 32.64 g‧L−1, and it increases to 34.76 g‧L−1 after adding enzymes. Meanwhile, the higher heating value of Gracilaria increases from 10.884 MJ‧kg−1 to 12.620 MJ‧kg−1 after undergoing alkaline pretreatment. After the acid and enzyme hydrolysis processes, it increases to 15.164 MJ‧kg−1. The solid biofuel's calorific value increases by 39 % from the three-stage processes. The liquid product combined with Saccharomyces cerevisiae can produce bioethanol, while the produced hydrochar can be used as a solid fuel. This research promotes the development of macroalgal biomass for energy and environmental applications, thereby advancing the circular bioeconomy. © 2024 The Institution of Chemical Engineers

关键词： Ethanol

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Mitigating Cascading Effects in Large Adversarial Graph Environments

arXiv

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arXiv 2024年

作者： Cunningham, James D. Tucker, Conrad S. Department of Mechanical Engineering Carnegie Mellon University PittsburghPA15213 United States Departments of Mechanical Engineering Machine Learning Robotics and Biomedical Engineering PittsburghPA15213 United States

A significant amount of society’s infrastructure can be modeled using graph structures, from electric and communication grids, to traffic networks, to social networks. Each of these domains are also susceptible to the cascading spread of negative impacts, whether this be overloaded devices in the power grid or the reach of a social media post containing misinformation. The potential harm of a cascade is compounded when considering a malicious attack by an adversary that is intended to maximize the cascading impact. However, by exploiting knowledge of the cascading dynamics, targets with the largest cascading impact can be preemptively prioritized for defense, and the damage an adversary can inflict can be mitigated. While game theory provides tools for finding an optimal preemptive defense strategy, existing methods struggle to scale to the context of large graph environments because of the combinatorial explosion of possible actions that occurs when the attacker and defender can each choose multiple targets in the graph simultaneously. The proposed method enables a data-driven deep learning approach that uses multi-node representation learning and counterfactual data augmentation to generalize to the full combinatorial action space by training on a variety of small restricted subsets of the action space. We demonstrate through experiments that the proposed method is capable of identifying defense strategies that are less exploitable than SOTA methods for large graphs, while still being able to produce strategies near the Nash equilibrium for small-scale scenarios for which it can be computed. Moreover, the proposed method demonstrates superior prediction accuracy on a validation set of unseen cascades compared to other deep learning approaches. © 2024, CC BY.

关键词： Game theory

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DROPLET-BASED MICROFLUIDIC SYNTHESIS OF FUNCTIONAL VASCULARIZED HYDROGEL MICROSPHERES 26

DROPLET-BASED MICROFLUIDIC SYNTHESIS OF FUNCTIONAL VASCULARI...

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26th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2022

作者： Zhan, Zhen Liu, Zeyang Li, Jianjie Zhang, Wenxuan Hu, Chengzhi Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Southern University of Science and Technology China

ISBN: (纸本)9781733419048

This paper proposes a droplet-based microfluidic method to generate hydrogel microspheres with interior undulated wavy or spiral canals for 3D cell culture. Human umbilical vein endothelial cells (HUVECs) were cultured in the interior canals of the hydrogel microspheres and formed monolayers on the surface of the spiral canals, mimicking native blood vessel configurations. The fabricated heterogeneous spheroids with spiral blood vessel lumen were also demonstrated to build spirally vascularized bone tissue. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

关键词： Microfluidics

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Path Tracing and Validation of Omni Wheeled Mini Robot Using Visual Feedback

Path Tracing and Validation of Omni Wheeled Mini Robot Using...

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International Conference on Advanced Computer Control, ICACC

作者： Aftaab Ahamed Karthik Jayaraj Shibin Fazil Nikitha S Sudheer A P Robotics Interest Group Mechatronics/Robotics Laboratory National Institute of Technology Calicut Mechanical Engineering Department Mechatronics/Robotics Laboratory National Institute of Technology Calicut

ISBN: (数字)9798350379136

ISBN: (纸本)9798350379143

Holonomic drives are gaining popularity in many fields due to their versatility in various industrial applications. The ability of the holonomic drive robots to move in all directions makes it distinct from other drive mechanisms. Open-loop control of omnidirectional bots can be achieved with relative ease whereas automating it is not as easy. When trying to create an automated system with lower cost, off the shelf components and hardware, other problems may arise as a result of the poor performance of the components. Here a three wheeled omnidirectional robot that can trace a predefined path without human intervention has successfully been developed.

关键词： Location awareness Visualization Costs Service robots Debugging Drives Hardware Mobile robots Robots Wireless fidelity

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