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IEEE International Conference on robotics and Biomimetics

作者： Jin Dai Yangyang Du Weiwei Zhao Chongjing Cao Yingtian Li Xing Gao School of Mechanical and Electrical Engineering Wuhan University of Technology Wuhan Research Centre for Medical Robotics and Minimally Invasive Surgical Devices Shenzhen Institutes of Advanced Technology (SIAT) Chinese Academy of Sciences Shenzhen China

Typical Fluidic elastomer actuators use conventional rigid air-compression systems that restrict their application in wearable devices. In this study, we propose a soft diaphragm pump driven by circular dielectric elastomer (DE) as the active diaphragm coupled with magnetic attraction as nonlinear antagonistic mechanism to improve amplitude. By taking the principle of volume change in diaphragm chamber together with two check-valves on both sides, directional pumping is achieved. Despite the presence of damping in the passive valves, the flexible pump still exhibits a good output performance at the resonance of DE. Furthermore, by optimizing the distance between the magnets and increasing the applied electric field strength, the output performance of the flexible pump can reach a maximum output pressure of 28 mbar and a peak gas flow rate of 0.24 L/min at an applied electric field of 60 MV/m.

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Present state of 3D printing from glass

Present state of 3D printing from glass

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作者： Hotař, Vlastimil Stará, Marie Máková, Veronika Nikendey Holubová, Barbora Department of Glass Producing Machines and Robotics Faculty of Mechanical Engineering Technical University of Liberec Studentská 1402/2 Liberec461 17 Czech Republic Department of Nanochemistry Institute for Nanomaterials Advanced Technologies and Innovation Technical University of Liberec Studentská 1402/2 Liberec461 17 Czech Republic

This paper deals with the issue of additive technologies using glass. At the beginning, our research dealt with a review of the current state and specification of potentially interesting methods and solutions. At present, this technology is being actively developed and studied in glass research. However, as the project started at the Department of Glass Producing Machines and robotics, the following text will be more focused on the existing 3D printing machinery and basic technological approaches. Although "additive manufacturing"in the sense of adding materials has been used in glass manufacturing since the beginning of the production of glass by humans, the term additive manufacturing nowadays refers to 3D printing. Currently, there are several approaches to 3D printing of glass that have various outstanding advantages, but also several serious limitations. The resulting products very often have a high degree of shrinkage and rounding (after sintering), and specific shape structures (after the application in layers), but they generally have a large number of defects (especially bubbles or crystallization issues). Some technologies do not lead to the production of transparent glass and, therefore, its optical properties are significantly restricted. So far, the additive manufacturing of glass do not produce goods that are price competitive to goods produced by conventional glass-making technologies. If 3D glass printing is to be successful as an industrial and/or highly aesthetically valuable method, then it must bring new and otherwise unachievable features and properties, as with 3D printing of plastic, metal, or ceramics. Nowadays, these technologies promise to be such a tool and are beginning to attract more and more interest. © 2021 IUPAC & De Gruyter. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. For more information, please visit: http://***/licenses/by-nc-nd/4.0/.

关键词： Glass

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CDM-MPC: An Integrated Dynamic Planning and Control Framework for Bipedal Robots Jumping

arXiv

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arXiv 2024年

作者： He, Zhicheng Wu, Jiayang Zhang, Jingwen Zhang, Shibowen Shi, Yapeng Liu, Hangxin Sun, Lining Su, Yao Leng, Xiaokun Department of Computer Science Harbin Institute of Technology Harbin150001 China Beijing100080 China School of Mechatronics Engineering Harbin Institute of Technology Harbin150080 China Jiangsu Provincial Key Laboratory of Advanced Robotics School of Mechanical and Electric Engineering Soochow University Suzhou215000 China

Performing acrobatic maneuvers like dynamic jumping in bipedal robots presents significant challenges in terms of actuation, motion planning, and control. Traditional approaches to these tasks often simplify dynamics to enhance computational efficiency, potentially overlooking critical factors such as the control of centroidal angular momentum (CAM) and the variability of centroidal composite rigid body inertia (CCRBI). This paper introduces a novel integrated dynamic planning and control framework, termed centroidal dynamics model-based model predictive control (CDM-MPC), designed for robust jumping control that fully considers centroidal momentum and non-constant CCRBI. The framework comprises an optimization-based kinodynamic motion planner and an MPC controller for real-time trajectory tracking and replanning. Additionally, a centroidal momentum-based inverse kinematics (IK) solver and a landing heuristic controller are developed to ensure stability during high-impact landings. The efficacy of the CDM-MPC framework is validated through extensive testing on the full-sized humanoid robot KUAVO in both simulations and experiments. Copyright © 2024, The Authors. All rights reserved.

关键词： Model predictive control

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Analysis of Lower Extremity Shape Characteristics in Various Walking Situations for the Development of Wearable Robot

Analysis of Lower Extremity Shape Characteristics in Various...

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

作者： Joohyun Park Ho Seon Choi Hyunki In Center for Healthcare Robotics Korea institute of science and technology Seoul Republic of Korea Department of Mechanical Engineering Korea Advanced Institute of Science and Technology Daeieon Republic of Korea Department of Intelligent Mechatronics Engineering Sejong University Seoul Republic of Korea

A strap is a frequently utilized component for securing wearable robots to their users in order to facilitate force transmission between humans and the devices. For the appropriate function of the wearable robot, the pressure between the strap and the skin should be maintained appropriately. Due to muscle contraction, the cross-section area of the human limb changes according to the movement of the muscle. The cross-section area change causes the change in the pressure applied by the strap. Therefore, for a new strap design to resolve this, it is necessary to understand the shape change characteristics of the muscle where the strap is applied. In this paper, the change in the circumference of the thigh and the calf during walking was measured and analyzed by multiple string pot sensors. With a treadmill and string pot sensors using potentiometers, torsion springs, and leg circumference changes were measured for different walking speeds and slopes. And, gait cycles were divided according to a signal from the FSR sensor inserted in the right shoe. From the experimental results, there were changes in the circumference of about 8.5mm and 3mm for the thigh and the calf, respectively. And we found tendencies in various walking circumstances such as walking speed and degree of the slope. It is confirmed that they can be used for estimation algorithms of gait cycles or gait circumstances.

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An Untethered Soft Robotic Gripper with Adjustable Grasping Modes and Force Feedback

An Untethered Soft Robotic Gripper with Adjustable Grasping ...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Yang, Yang Zhu, Honghui Liu, Jia Li, Yingtian Zhou, Jianshu Ren, Tao Ren, Yi School of Automation Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China Jiangsu Province Engineering Research Center of Intelligent Meteorological Exploration Robot China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Hong Kong Hong Kong Hong Kong Center for Logistics Robotics Hong Kong Hong Kong School of Mechanical and Electrical Engineering Chengdu University of Technology Chengdu610059 China Advanced Manufacturing Lab Huawei Technologies Shenzhen China

ISBN: (纸本)9781665481090

In this paper, we propose a three-finger soft robotic gripper, which adopts an untethered and under-actuated design with simple structure and easy operation. The rotation of two servomotors is used to control the positions of the fingers, which provides the fingers with adjustable grasping modes and improves the adaptation of the gripper to objects with different shapes. A pressure sensor is integrated at the end of the finger to provide force feedback, which is used to detect the contact force when grasping the object and enables the gripper to provide the proper grasping force. The experimental section characterizes the bending of the soft robotic finger, and the gripper is integrated at the end of a collaborative robotic arm to demonstrate its adjustable grasping posture and force feedback function. The soft robotic gripper is expected to be used in a variety of scenarios, such as service robot, food industry or garbage sorting. © 2022 IEEE.

关键词： Grippers

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Sound-Based Identification and Sorting of Flexible Plastic Packaging for Recycling

SSRN

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SSRN 2023年

作者： Roche, Kevin John Johnson, Sawyer Fleming, Kieran Laboratory for Advanced Manufacturing Simulation and Robotics School of Mechanical and Materials Engineering University College Dublin Ireland University of Colorado Boulder United States Apoyo Ltd. Co. Cavan Bailieborough Ireland

Highlights• Flexible plastic packaging can be sorted based on sound.• Low-cost equipment and simple machine learning models can be effective.• HDPE, LDPE, and PP identified with 86-90% accuracy.• Suitable for real-tim... 详细信息

关键词： Plastic recycling

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Miniature Reconfigurable Modular Soft Robots Using Liquid Crystal Elastomer Actuation

Miniature Reconfigurable Modular Soft Robots Using Liquid Cr...

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ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots, ReMAR

作者： Huayu Zhang Jiajun An Tianle Pan Upinder Kaur Zhijian Wang Xuchen Wang Qiguang He Xin Ma Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong SAR Multiscale Medical Robotics Centre Hong Kong SAR Department of Agricultural and Biological Engineering Purdue University USA Key Laboratory of Aerospace Advanced Materials and Performance Ministry of Education School of Materials Science and Engineering Beihang University China

ISBN: (数字)9798350395969

ISBN: (纸本)9798350395976

Soft robotics is rapidly evolving, fueled by advancements in controllable materials. Liquid crystal elastomers (LCEs) stand out with their exceptional actuation capabilities, ease of processing, and built-in programmability. However, current LCE robots struggle with limited dexterity and adaptability, hindering their real-world potential. We address this limitation by introducing a novel modular design approach that unlocks the full potential of LCEs. Our miniature, highly deformable soft robot utilizes reconfigurable LCE modules for bending and twisting, enabling enhanced manipulability through serial combinations. Demonstrating its dexterity, the modular robot performs intricate fingertip manipulation, allowing a miniature gripper to rotate a small object. This achievement highlights the reconfigurability and utility of our system, paving the way for more dexterous and versatile LCE-based robots.

关键词： Elastomers Soft robotics Bending Grippers

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The multifaceted approach to embodied intelligence in robotics

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Science robotics 2025年第102期10卷 eadx2731页

作者： Laschi, Cecilia Department of Mechanical Engineering Advanced Robotics Centre National University of Singapore Singapore Singapore

Embodied intelligence refers to the aspects of sensory-motor behavior that reside in the body, relying on its mechanical properties and physical interactions with the environment (1). Here, motor control is not entirely managed by the computing system—whether it is the nervous system of an animal or the controller of a robot. Instead, motor behavior is partially shaped mechanically by external forces acting on the body. Nature offers numerous examples of embodied intelligence that have been inspiring robotics for years. When we walk, our compliant knees can compensate for small changes in terrain mechanically, with no involvement of the central nervous system. When we grasp an object, our fingers adapt to its shape mechanically, without controlling the movement of each phalanx.

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A Convolutional Spiking Neural Network with Adaptive Coding for Motor Imagery Classification

SSRN

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SSRN 2023年

作者： Liao, Xiaojian Wu, Yuli Wang, Zi Wang, Deheng Zhang, Hongmiao The Jiangsu Provincial Key Laboratory of Advanced Robotics School of Mechanical and Electric Engineering Soochow University Suzhou215000 China School of Basic Medical Sciences Shanghai University of Traditional Chinese Medicine Shanghai201203 China

Motor imagery (MI) signal classification is crucial for brain-computer interfaces (BCI). The third-generation neural network, spiking neural network (SNN), has rich neurodynamic properties in the spatiotemporal domain, and therefore it is more suitable for processing EEG signals. However, the feature extraction capability of the SNN previously applied to MI signal classification is limited by its structure, and the model's classification accuracy is not comparable to the state-of-the-art algorithms. In this paper, we propose a spiking neural network model called SCNet, which combines the feature extraction capability of CNN with the biological interpretability of SNN, making the model structurally closer to the biological neuronal dynamical system and improving the classification accuracy. SCNet reduces information loss by adaptive coding with learnability and solves the training difficulties of spiking neural networks by surrogate gradient learning. We evaluated the performance of the proposed SCNet on three typically representative motor imagery datasets. The validation shows that the model outperforms state-of-the-art SNN-based MI classification methods and various ANN and machine learning methods. The experimental results demonstrate the generality and effectiveness of the proposed motor imagery EEG signal classification model. Better classification results can be obtained by designing a well-structured spiking neural network. © 2023, The Authors. All rights reserved.

关键词： Feature extraction

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A robust optimization modelling approach for dairy production planning

A robust optimization modelling approach for dairy productio...

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2020 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2020

作者： Soolaki, Majid Hargaden, Vincent Laboratory for Advanced Manufacturing Simulation and Robotics School of Mechanical and Materials Engineering University College Dublin Ireland

ISBN: (纸本)9781713827818

The constituent components of raw milk from dairy cows, especially fat and protein, tend to vary continuously throughout the year. These raw milk constituents then influence the decision around which final dairy products it is possible to produce. Using the concept of seasonal variation in raw milk composition, this paper describes the development of an optimisation model with the aim of making better supply chain planning decisions for dairy processors. A robust optimization approach addresses the uncertainty of parameters and presents optimal plans based on various demand and supply scenarios. The results of the proposed method aid the managerial decision-making process in relation to the most profitable products to produce based on real customer demand. © Proceedings of the 2020 IISE Annual. All Rights Reserved.

关键词： Supply chains

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