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检索条件"机构=National Robotics Engineering Center and Robotics Institute"

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A Comprehensive Methodology for Assessing the Economic Viability of EV Charging Infrastructure in Brazil

A Comprehensive Methodology for Assessing the Economic Viabi...

引用

6th International Conference on Smart Power and Internet Energy Systems, SPIES 2024

作者： Neto, Daywes Pinheiro Coimbra, António Paulo De Almeida, Anibal T. Almeida, Tony R. Moura, Pedro Ucker, Leticia C. Gomes, Raphael A. Magalhães, Alana S. Center for Experimental and Technological Research and Studies Federal Institute of Goiás Brazil Institute of Systems and Robotics University of Coimbra Dpt. of Electrical and Computer Engineering Portugal

ISBN: (纸本)9798350368864

This study proposes a comprehensive methodology to assess the economic viability of electric vehicle (EV) charging infrastructure projects in Brazil, specifically targeting connections with a capacity of up to 112.5 kW, which are subject to flat electricity tariffs. The methodology employs a novel EV energy consumption model, integrates the regulatory framework of net metering and relevant tax considerations, explores the potential cost-saving benefits of photovoltaic (PV) system integration, and utilizes key economic indicators like Net Present Value and Discounted Payback Time to quantify project profitability. By accounting for a set of EV demand scenarios (low, moderate, and high), the methodology provides a multifaceted assessment of project viability. A case study demonstrates the methodology's application, highlighting the potential economic benefits of such investments. The results suggest that the minimum charging service fee required for economic viability ranges from 0.17 to 0.29 USD/kWh, with a clear cost advantage associated with PV integration observed across all scenarios. © 2024 IEEE.

关键词： Energy utilization

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Under-actuated Robotic Gripper with Multiple Grasping Modes Inspired by Human Finger

Under-actuated Robotic Gripper with Multiple Grasping Modes ...

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

作者： Jihao Li Tingbo Liao Hassen Nigatu Haotian Guo Guodong Lu Huixu Dong Grasp Lab School of Mechanical Engineering Zhejiang University Hangzhou China Robotics Institute of Zhejiang University Hangzhou China College of Design and Engineering National University of Singapore Singapore

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Under-actuated robot grippers, as a pervasive tool of robots, have become a considerable research focus. Despite their simplicity of mechanical design and control strategy, they suffer from poor versatility and weak adaptability, making widespread applications limited. To better address relevant research gaps, we present a novel 3-finger linkage-based gripper that realizes retractable and reconfigurable multi-mode grasps driven by a single motor. Firstly, inspired by the changes occurred in the contact surface with a human finger moving, we artfully design a slider-slide rail mechanism as the phalanx to achieve retraction of each finger, allowing for better performance in the enveloping grasping mode. Secondly, a reconfigurable structure is constructed to broaden the grasping range of objects’ dimensions for the proposed gripper. By adjusting the configuration and gesture of each finger, the gripper can achieve five grasping modes. Thirdly, the proposed gripper is solely actuated by a single motor, yet it can be capable of grasping and reconfiguring simultaneously. Finally, various experiments on grasps of slender, thin, and large-volume objects are implemented to evaluate the performance of the proposed gripper in practical scenarios, which demonstrates the excellent grasping capabilities of the gripper.

关键词： Rails Couplings Fingers Grasping Switches Motors Grippers Standards Intelligent robots

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ColorPCR: Color Point Cloud Registration with Multi-Stage Geometric-Color Fusion

ColorPCR: Color Point Cloud Registration with Multi-Stage Ge...

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Juncheng Mu Lin Bie Shaoyi Du Yue Gao BNRist THUIBCS School of Software Tsinghua University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications and Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Point cloud registration is still a challenging and open problem. For example, when the overlap between two point clouds is extremely low, geo-only features may be not suf-ficient. Therefore, it is important to further explore how to utilize color data in this task. Under such circumstances, we propose ColorPCR for color point cloud registration with multi-stage geometric-color fusion. We design a Hier-archical Color Enhanced Feature Extraction module to ex-tract multi-level geometric-color features, and a GeoColor Superpoint Matching Module to encode transformation-invariant geo-color global context for robust patch corre-spondences. In this way, both geometric and color data can be used, thus leading to robust performance even under extremely challenging scenarios, such as low overlap between two point clouds. To evaluate the performance of our method, we colorize 3DMatch/3DLoMatch datasets as Color3DMatch/Color3DLoMatch and evaluations on these datasets demonstrate the effectiveness of our proposed method. Our method achieves state-of-the-art registration recall of 97.5%/88.9% on them.

关键词： Point cloud compression Computer vision Accuracy Image color analysis Feature extraction Pattern recognition Task analysis

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A Novel Approach for Efficient Gaussian Mixture Model using Dynamics-motivated Optimal Excitation

A Novel Approach for Efficient Gaussian Mixture Model using ...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Taehoon Kim Juwon Jeong Taejune Kong Hyunwook Lee Sehoon Oh Department of Robotics and Mechatronics Engineering DGIST (Daegu Gyeongbuk Institute of Science and Technology) Daegu Republic of Korea School of Mechatronics Engineering Gyeongsang National University Jinju Republic of Korea

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

EffiDynaMix, a novel, efficient, gray-box, nonparametric dynamics modeling method, integrates mathematical dynamics with Gaussian Mixture Model (GMM) for simplified training data creation and improved generalization. It outperforms traditional methods like conv-GMM, GP, and LSTM in training efficiency and accuracy with new data. By leveraging dynamic equations, EffiDynaMix enhances learning efficiency and adaptability, offering advancements in robotic system precision and computational efficiency, leading to faster and more responsive robots.

关键词： Training Industrial electronics Adaptation models Service robots Computational modeling Training data Mathematical models

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Internet of Things (IoT) and Machine Learning (ML) in Cyber-Security 2

Internet of Things (IoT) and Machine Learning (ML) in Cyber-...

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2nd IEEE International Conference on Artificial Intelligence of Things and Crowdsensing, AIoTCs 2022

作者： Abdelrahim, Malik Al-Turjman, Fadi Research Center for Ai and IoT Near East University Artificial Intelligence Engineering Department Nicosia Cyprus Artificial Intelligence Engineering Department Ai and Robotics Institute Near East University Mersin10 Turkey

ISBN: (纸本)9798350334104

With the technological advancement, the world is going through, at such a high pace, new challenges arise that might require new approaches. ML is, without a doubt, on the lead of technology, as it is evolving with minimal human intervention. However, new models of ML are crucial to preventing hackers from manipulating data. It is true that with new models, new gates for attacks are opened, which is why ML security must follow the same pace in evolving. In this paper, a brief introduction to ML and ML security will be discussed to give an insight on the topic, before going through a more specific point;the challenges faced by ML security. By introducing these terms, the reader will come to grasp the importance of ML security, and the huge role it plays when it comes to protecting data against hackers. However, this by no means indicates that it is flawless;on the contrary, there are flaws in the methods used in our present day, which is another topic this paper will give an insight on. Our main focus in this paper will be supervised learning due to its application in security. Algorithms used in ML models is the main gate that hackers use to breach the system, for this precise reason, engineers and experts are challenged to come with new algorithms, as we will conclude this work. © 2022 IEEE.

关键词： Machine learning

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Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement

Salience DETR: Enhancing Detection Transformer with Hierarch...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Xiuquan Hou Meiqin Liu Senlin Zhang Ping Wei Badong Chen National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China College of Electrical Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

DETR-like methods have significantly increased detection performance in an end-to-end manner. The main-stream two-stage frameworks of them perform dense self-attention and select a fraction of queries for sparse cross-attention, which is proven effective for improving performance but also introduces a heavy computational burden and high dependence on stable query selection. This paper demonstrates that suboptimal two-stage selection strategies result in scale bias and redundancy due to the mismatch between selected queries and objects in two-stage initial-ization. To address these issues, we propose hierarchical salience filtering refinement, which performs transformer encoding only on filtered discriminative queries, for a bet-ter trade-off between computational efficiency and precision. The filtering process overcomes scale bias through a novel scale-independent salience supervision. To com-pensate for the semantic misalignment among queries, we introduce elaborate query refinement modules for stable two-stage initialization. Based on above improvements, the proposed Salience DETR achieves significant improvements of +4.0% AP, +0.2% AP, +4.4% AP on three challenging task-specific detection datasets, as well as 49.2% AP on COCO 2017 with less FLOPs. The code is available at https://***/xiuqhou/Salience-DETR.

关键词： Computer vision Filtering Redundancy Semantics Object detection Detectors Transformers

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Towards MR-Safe Concentric Bellows-Based Hydrostatic Linear Actuator for a Needle Driver

Towards MR-Safe Concentric Bellows-Based Hydrostatic Linear ...

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

作者： Kwan Kit Lin Yufu Qiu Kim Yan Qingpeng Ding Shing Shin Cheng Department of Mechanical and Automation Engineering and CUHK T Stone Robotics Institute The Chinese University of Hong Kong Hong Kong Shun Hing Institute of Advanced Engineering and Multi-Scale Medical Robotics Center The Chinese University of Hong Kong Hong Kong

Magnetic resonance imaging (MRI) is increasingly used for robotic needle-based clinical diagnosis and therapy due to its high resolution and high soft tissue contrast. A needle driver therefore becomes an essential part of these MRI -guided robotic systems to perform in-bore needle placement under continuous MR imaging. However, existing actuator designs for needle drivers are constrained by the high magnetic field and the bore size of the MR scanner, and most lack high- performance capability, especially in terms of large output force and long stroke. In this work, we introduce an MR-safe concentric bellows linear actuator (CBLA) with improved performance over the existing designs. This soft actuator achieves 45N output force, 77 % stroke-length ratio for the bellows, and around 250% stroke-diameter ratio. A mathematical model was built to characterize the behavior of the actuator to provide guidance for the actuator design. The fabrication and experimental evaluation of the actuator are also presented. The results demonstrate the effectiveness of the CBLA design and the strong potential of its application in MR-guided surgical procedures.

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Human Hand Gesture Recognition System Using Body Sensor Network 4

Human Hand Gesture Recognition System Using Body Sensor Netw...

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4th International Conference on robotics and Automation in Industry, ICRAI 2021

作者： Maheen, Asra Bin Shahzad, Moosa Asif, M. Usama Ahmad, Syed Fasih Zafar, Saqib Maqbool, H. Farhan Usman, Muhammad Arshad, Hira Department of Mechanical Mechatronics And Manufacturing Engineering Faisalabad Pakistan Human-Centered Robotics Lab National Center of Robotics And Automation Lahore Pakistan Pakistan Engineering Council Islamabad Pakistan Department of Mechanical Mechatronics And Manufacturing Engineering Faisalabad Pakistan

ISBN: (纸本)9781665423434

Wearable technology has gained massive popularity for applications in healthcare in recent years. Body sensor network (BSN) includes wearable sensors such as Myoware muscle sensor that can capture electromyography (EMG) signal from human muscles during a movement. This study involves the control of a 3d prosthetic hand using EMG data of basic hand gestures from healthy subjects and operating the prosthetic hand with this classified data. Artificial Neural Networks (ANN) are biologically inspired computational networks which help to build predictive models from large databases. Backpropagation combined with feedforward ANN is used to classify data here. Classification results showed an accuracy of about 91% for four-hand gestures - hand closed, hand open, pointing index finger, and pinch motion. The BSN-based prosthetic hand can facilitate rehabilitation of amputees, perform surgery using recorded EMG data from a surgeon's hands and reduce industrial manpower in the future. © 2021 IEEE.

关键词： Neural networks

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Swing-Up of a Weakly Actuated Double Pendulum via Nonlinear Normal Modes

Swing-Up of a Weakly Actuated Double Pendulum via Nonlinear ...

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European Control Conference (ECC)

作者： Arne Sachtler Davide Calzolari Maximilian Raff Annika Schmidt Yannik P. Wotte Cosimo Della Santina C. David Remy Alin Albu-Schäffer German Aerospace Center (DLR) Institute of Robotics and Mechatronics Münchener Straβe 20 Oberpfaffenhofen Germany Department of Computer Engineering Technical University of Munich (TUM) Garching Germany University of Stuttgart Institute for Nonlinear Mechanics Stuttgart Germany Robotics & Mechatronics Group University of Twente Enschede The Netherlands Department of Cognitive Robotics Delft University of Technology (TU Delft) Delft The Netherlands

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

We identify the nonlinear normal modes spawning from the stable equilibrium of a double pendulum under gravity, and we establish their connection to homoclinic orbits through the unstable upright position as energy increases. This result is exploited to devise an efficient swing-up strategy for a double pendulum with weak, saturating actuators. Our approach involves stabilizing the system onto periodic orbits associated with the nonlinear modes while gradually injecting energy. Since these modes are autonomous system evolutions, the required control effort for stabilization is minimal. Even with actuator limitations of less than 1% of the maximum gravitational torque, the proposed method accomplishes the swing-up of the double pendulum by allowing sufficient time.

关键词： Actuators Torque Tensors Modal analysis Motors Orbits Generators

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Dual Multilayer Extension Actuator for High Extension and High Compression Force Applications

Dual Multilayer Extension Actuator for High Extension and Hi...

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IEEE International Conference on Soft robotics (RoboSoft)

作者： Jonathan William Ambrose Dylan Sin You Cheah Raye Chen-Hua Yeow Department of Biomedical Engineering Advanced Robotics Center at the National University of Singapore (NUS) Singapore Department of Biomedical Engineering Nanyang Polytechnic (NYP) Singapore

Soft robotic actuators possess several unique characteristics, such as being generally compliant and lightweight, making them suitable for safe human interaction to be deployed in various industries. However, they are often designed for an intended purpose, making them impractical for a different task. This paper aims to introduce a new way of utilising a new class of soft silicone actuators capable of incorporating them into applications that require both pushing and pulling. The dual multilayer extension actuator (DMEA) is compact and lightweight at 8 g, capable of an extension ratio of 300% and a high pulling force-to-weight ratio of 200 with the assistance of vacuum pressure at 30% extension ratio. The fabrication of the DMEA is described in detail and followed by characterisation tests of the DMEA compared to the FEA model. Finally, we showcase the DMEA pulling a 3D-printed arm as a potential assistive device and demonstrate the DMEA versatility by deploying the DMEA onto everyday household products like scissors and kitchen tongs.

关键词： Industries Fabrication Actuators Force Dynamics Soft robotics Nonhomogeneous media

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