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

作者： Xia, Yanming Song, Chao Meng, Yingchao Xue, Peng deMello, Andrew J. Gao, Quan Stavrakis, Stavros Ma, Shenglin Cao, Xiaobao Department of Mechanical & Electrical Engineering Xiamen University Xiamen China Institute for Chemical and Bioengineering ETH Zürich Zürich8093 Switzerland Institute of Robotics and Intelligent Systems ETH Zürich Zürich8006 Switzerland Guangzhou Laboratory Guangdong Guangzhou510320 China

ISBN: (纸本)9781733419048

This paper presents and assesses an addressable electrowetting centrifugal (EWC) valve, which can rapidly and selectively open through (remote) control of the applied electric field. The utility of EWC valves is showcased by the implementation of fluid complexly controlling and CD4 cell antigens detection. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized systems for Chemistry and Life Sciences. All rights reserved.

关键词： Wetting

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Serial Chain Hinge Support for Soft, Robust and Effective Grasp

arXiv

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arXiv 2022年

作者： Stuhne, Dario Vuletić, Jelena Car, Marsela Orsag, Matko LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 Zagreb10000 Croatia

This paper presents a serial chain hinge support, a rigid but flexible structure that improves the mechanical performance and robustness of soft-fingered grippers. Gravity can reduce the integrity of soft fingers in horizontal approach, resulting in lower maximum payload caused by a large deflection of fingers. To substantiate our claim we performed several experiments on payload and deflection of the SofIA gripper under both horizontal and vertical approach. In addition, we show that this reinforcement does not impede the original compliant behavior of the gripper, maintaining the original kinematic model functionality. We showcase the proprioceptive and exteroceptive capabilities (RGB-D camera and flex sensor) for two opposing manipulation problems: grasping small and large objects. Finally, we validated the improved SofIA gripper in agricultural and everyday activities. © 2022, CC BY.

关键词： Grippers

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Feedforward Backpropagation Artificial Neural Network for Modeling the Forward Kinematics of a Robotic Manipulator

Feedforward Backpropagation Artificial Neural Network for Mo...

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Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT), International Conference o

作者： Rania Bouzid Jyotindra Narayan Hassène Gritli Higher Institute of Information and Communication Technologies University of Carthage RISC Laboratory (LR16ES07) Tunis Tunisia Mechatronics and Robotics Laboratory Department of Mechanical Engineering Indian Institute of Technology Guwahati Guwahati India Laboratory of Robotics Informatics and Complex Systems (RISC Lab - LR16ES07) National Engineering School of Tunis University of Tunis El Manar Tunis Tunisia

Determining an end-effector position and orientation, known as forward kinematics (FK), is a crucial aspect of robotic manipulation. This research addresses the FK problem using a Feedforward Backpropagation Artificial Neural Network (FFBP-ANN) and examines the network’s performance with different hyperparameters. The input of the FFBP-ANN is primarily formed using three different datasets: fixed-step values, random values, and sinusoidal-signal based values, for a 2-DOF robotic manipulator. The output of the FFBP-ANN is evaluated using FK formulation of the robot manipulator. Thereafter, the FFBP-ANN is trained utilizing the input-output training dataset using The Neural Network Toolbox for MATLAB. The network’s potential is investigated by varying the critical hyperparameters, including the number of hidden neurons and the number of hidden layers. Moreover, the effectiveness of the proposed FFBP-ANN is investigated with three different training optimizers including the utilization of Levenberg-Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient optimization algorithms. During training, by adjusting the network’s weights and biases iteratively, the backpropagation technique allows the network to effectively learn and comprehend the relationship between joint positions and Cartesian coordinates. The comparative results offer valuable insights into the strengths and limitations of different ANN architectures when applied to solving FK problems. In this way, this study focuses on exploring the application of the FFBP-ANN in resolving FK challenges and assisting in the identification of appropriate network types for path-planning tasks.

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Selection of relevant mode of thin and soft parts measurements on machines with multisensor possibility 23

Selection of relevant mode of thin and soft parts measuremen...

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23rd International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2023

作者： Harmatys, Wiktor Gaska, Adam Gaska, Piotr Gruza, Maciej Marxer, Michael Cracow University of Technology Faculty of Mechanical Engineering Laboratory of Coordinate Metrology al. Jana Pawla II 37 Cracow31-864 Poland Department of Manufacturing Systems Faculty of Mechanical Engineering and Robotics AGH University of Science and Technology al. Mickiewicza 30 Krakow30-059 Poland Eastern Switzerland University of Applied Sciences Institute for Production Metrology Materials and Optics Werdenbergstrasse 4 SG BuchsCH-9471 Switzerland

ISBN: (纸本)9781998999132

This paper presents measurements of thin and soft parts that are easily deformable under contact force related to tactile measurement. Few types of such elements, widely used in practice, were chosen and measured on multisensor CMM using low force tactile probe, video probe and chromatic white light sensor. Measurement procedure included aligning of the workpiece based on points measured using different sensors and performing measurements according to multiple-measurement strategy method. Values of repeatability determined for measurement results from different sensors were compared. Differences in obtained repeatability values are significant. Discussion of aftermaths related to use of various types of sensors is also included in the paper. © 2023 Euspen Headquarters.

关键词： Probes

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Design and preliminary testing of a piezoelectric-based sole energy harvester

Design and preliminary testing of a piezoelectric-based sole...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Wang, Yidi Zhao, Xuan Shi, Qiuyu Liao, Haisu Wu, Xinyu Gao, Fei Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin999077 Hong Kong

ISBN: (纸本)9781665481090

Harvesting energy from the human body to replenish existing energy sources is receiving substantial attention. Recently scientists have been focusing on harvesting biomechanical energy from human feet during walking. This paper develops a piezoelectric-based sole energy harvester that is designed to be worn on the bottom of shoes to harvest energy, thus powering wearable electronic devices. Specifically, a cam with piezoelectric(PZT) stacks is mounted on the heel to scavenge energy during the heel strike. The cam can change the input's direction from the vertical direction to the horizontal direction. In addition, the output power of this part can be optimized or improved by generating a specified cam profile. A bimorph piezoelectric plate is installed on the forefoot to convert the toes' bending deformation into electricity. Herein, piezoelectric Macro Fiber Composites (MFC) are employed to capture the large deformation. Preliminary testing on a healthy subject is conducted to validate this design. The average power output of the harvester is 8.83 m W. © 2022 IEEE.

关键词： Cams

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Semantic Mapping Based on Visual SLAM with Object Model Replacement Visualization for Cleaning Robot

Semantic Mapping Based on Visual SLAM with Object Model Repl...

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IEEE International Conference on robotics and Biomimetics

作者： Zirui Wang Haiou Liao Zhenzhong Jia Jing Wu Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems they are also with Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology (SUSTech) Shenzhen China

ISBN: (纸本)9781665481106

Cleaning robots have been widely used in our daily life, achieving huge success in the service robot sector. The autonomous movement and decision-making of these robots directly depend on their environmental perception capability, which is implemented using SLAM (simultaneous localization and mapping) technique. In order to achieve better environmental perception and intelligent decision-making, it is necessary to introduce visual SLAM into cleaning robot and take full advantage of visual information to achieve higher-level perception, instead of sticking to current feature point or pixel level perception capability. In this paper, we propose a framework for semantic mapping with object model replacement visualization in indoor scenes for cleaning robot. We use an EKF-based method to fuse wheel odometry and visual odometry, and build a map representation for navigation in the framework. We obtain a semantic map by fusing object detection and point cloud segmentation. We also develop object model replacement for better visualization purposes. Finally, we conduct dataset tests and real experiments to validate our proposed framework.

关键词： Visualization Simultaneous localization and mapping Service robots Biological system modeling Semantics Decision making Wheels

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A Multi-Layer Software Architecture for Aerial Cognitive Multi-Robot systems in Power Line Inspection Tasks

A Multi-Layer Software Architecture for Aerial Cognitive Mul...

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2021 International Conference on Unmanned Aircraft systems, ICUAS 2021

作者： Silano, Giuseppe Bednar, Jan Nascimento, Tiago Capitan, Jesus Saska, Martin Ollero, Anibal Czech Technical University Faculty of Electrical Engineering Prague Czech Republic Universidade Federal da Paraiba Department of Computer Systems Brazil Grvc Robotics Laboratory University of Seville Spain

ISBN: (纸本)9780738131153

This paper presents a multi-layer software architecture to perform cooperative missions with a fleet of quad-rotors providing support in electrical power line inspection operations. The proposed software framework guarantees the compliance with safety requirements between drones and human workers while ensuring that the mission is carried out successfully. Besides, cognitive capabilities are integrated in the multi-vehicle system in order to reply to unforeseen events and external disturbances. The feasibility and effectiveness of the proposed architecture are demonstrated by means of realistic simulations. © 2021 IEEE.

关键词： Inspection

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Atomic Simulations of Tip-Based Nanomilling Process on Single Crystal Copper

SSRN

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SSRN 2022年

作者： Yan, Yongda Li, Zihan Wang, Jiqiang Geng, Yanquan The State Key Laboratory of Robotics and Systems Robotics Institute Harbin Institute of Technology Heilongjiang Harbin150080 China Center for Precision Engineering Harbin Institute of Technology Heilongjiang Harbin150001 China

An atomic force microscopy (AFM) tip-based scratch method has been used to machine 2D/3D micro-nanostructures. However, the machining efficiency is too low for being applied in a wide application. The AFM tip-based nanomilling approach has the advantage of higher efficiency due to a higher materials removal rate. This paper compares the materials removal mechanism between single scratch and nanomilling processes close to the atomic scale on single crystal copper surface using the molecular dynamics simulation. By analyzing the groove morphology, atomic flow behavior and variation of scratching forces, the materials removal mechanism is revealed in this study. Moreover, tip trajectory and sample crystallographic orientation effect on atomic removal are also studied by the analysis of relationship between the evolution of the subsurface defect and material removal. This work reveals the mechanism of the materials removal in nanomilling process in detail, which will greatly improve the ability of the tip-based nanomachining method. © 2022, The Authors. All rights reserved.

关键词： Molecular dynamics

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Multiple Sensor Fusion-Based Positioning Robot for Steam Generator Inspection

Multiple Sensor Fusion-Based Positioning Robot for Steam Gen...

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Sensor Technology and Control (ISSTC), International Symposium on

作者： Jingwei You Shouqi Wei Xiong Wu Jianquan Sun Department of Electrical Engineering Guilin University of Electronic Technology Guilin China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems Shenzhen China

Nuclear energy is presently the clean energy source most likely to massively displace fossil energy, and the secondary side of the steam generator is an important part of a nuclear power plant. Due to the small space of the secondary side of the steam generator and the confinement of the vessel, the precise positioning of the robot inside the steam generator cannot be achieved by a single sensor alone. This paper introduces a multi-sensor fusion steam generator secondary side inspection robot. Primary emphasis is on data fusion of multiple sensors, such as laser sensors, cameras, IMU, and wheel encoder. First of all, this paper integrates data from wheel encoder data and IMU data by using extended Kalman filtering (EKF), which decreases the drift error during the motion and enhances the robot positioning precision. Afterwards, we incorporate laser ranging sensors and camera picture data to enhance the overall spatial sensitivity of the robot through particle filtering algorithms. Experiments show that the robot works reliably and has high positioning accuracy.

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Intelligent Wireless Self-Sustained Sensing Cubic Node Toward AIOT Ready Smart City

Intelligent Wireless Self-Sustained Sensing Cubic Node Towar...

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Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS)

作者： Manjuan Huang Tingting Zhao Guoqing Jin Xiaojing Mu Huicong Liu Jiangsu Provincial Key Laboratory of Advanced Robotics School of Mechanical and Electrical Engineering Soochow University Suzhou CHINA Key Laboratory of Optoelectronic Technology & Systems Ministry of Education International R&D Center of Micro-nano Systems and New Materials Technology Chongqing University Chongqing CHINA

This paper presents an intelligent wireless self-sustained sensing cubic node, consisting of a rotational electromagnetic generator (R-EMG) for power supply and a versatile triaxial piezoelectric sensor (TPS) composed of three piezoelectric beams. This system enhances internet of things (IoT) sensing through cloud-based artificial intelligence (AI) computing. The cubic node provides power generation and multi-functional sensing capabilities, including vibration acceleration, frequency, and tilting angle. The design of the R-EMG ensures stable output at different rotational speeds, reaching a maximum output power of 66 mW at 550 rpm with an external load of 1.1 kΩ, allowing for self-sustaining energy generation for the node. Additionally, the cubic design enables the orthogonal placement of the three piezoelectric beams, enabling a broad response to vibrational energy from various directions. This flexibility allows for diverse applications across different frequencies and scenarios.

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