2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)最新文献_第10页

Multi-Robot Online Terrain Coverage under Communication Range Restrictions – An Empirical Study 通信距离限制下多机器人在线地形覆盖的实证研究

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551390

A. Gautam, Ankit Soni, V. S. Shekhawat, Sudeept Mohan

引用次数: 4

VLC-SE: Visual-Lengthwise Configuration Self-Estimator of Continuum Robots VLC-SE:连续体机器人纵向视觉构形自估计器

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551551

Hao Cheng, Bin Lan, Houde Liu, Xueqian Wang, Bin Liang

引用次数: 1

Extended Fabrication-Aware Convolution Learning Framework for Predicting 3D Shape Deformation in Additive Manufacturing 增材制造中三维形状变形预测的扩展制造感知卷积学习框架

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551545

Yuanxiang Wang, Cesar Ruiz, Qiang Huang

引用次数: 1

A Seamless Workflow for Design and Fabrication of Multimaterial Pneumatic Soft Actuators 多材料气动软执行器设计与制造的无缝工作流

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551668

Lawrence Smith, Travis Hainsworth, Zachary Jordan, Xavier Bell, R. MacCurdy

{"title":"A Seamless Workflow for Design and Fabrication of Multimaterial Pneumatic Soft Actuators","authors":"Lawrence Smith, Travis Hainsworth, Zachary Jordan, Xavier Bell, R. MacCurdy","doi":"10.1109/CASE49439.2021.9551668","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551668","url":null,"abstract":"Soft robotic actuators offer a range of attractive features relative to traditional rigid robots including inherently safer human-robot interaction and robustness to unexpected or extreme loading conditions. Soft robots are challenging to design and fabricate, and most actuators are designed by trial and error and fabricated using labor-intensive multi-step casting processes. We present an integrated collection of software tools that address several limitations in the existing design and fabrication workflow for pneumatic soft actuators. We use implicit geometry functions to specify geometry and material distribution, a GUI-based software tool for interactive exploration of computational network representations of these implicit functions, and an automated tool for generating rapid simulation results of candidate designs. We prioritize seamless connectivity between all stages of the design and fabrication process, and elimination of steps that require human intervention. The software tools presented here integrate with existing capabilities for multimaterial additive manufacturing, and are also forward-compatible with emerging automated design techniques. The workflow presented here is intended as a community resource, and aimed at lowering barriers for the discovery of novel soft actuators by experts and novice users. The data gathered from human-interaction with this tool will be used by future automation tools to enable fully-automated soft actuator design based on high-level specifications.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"178 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115442976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Incremental Abstraction - An Analytical and Algorithmic Perspective on Petri Net Reduction 增量抽象——Petri网约简的分析和算法视角

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551438

B. Lennartson

引用次数: 0

A Combinatorial Auctions Approach to Capacity Sharing in Collaborative Supply Chains 协同供应链产能共享的组合拍卖方法

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551538

J. C. Villumsen, Atsuki Kiuchi, Yuma Shiho, Junko Hosoda, Takahiro Ogura

引用次数: 0

Determination of Anchor Points for Efficient Long Load Transportation using Multi-Rotor Aerial Vehicles 多旋翼飞行器高效长载荷运输锚点的确定

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551675

Shubhankar Shobhit, S. AbhinayN., K. Das

引用次数: 0

Non-Destructive Failure Analysis of Power Devices via Time- Domain Reflectometry 基于时域反射法的电力器件无损失效分析

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551614

K. Sharma, Simon Kamm, V. Afanasenko, K. M. Barón, I. Kallfass

{"title":"Non-Destructive Failure Analysis of Power Devices via Time- Domain Reflectometry","authors":"K. Sharma, Simon Kamm, V. Afanasenko, K. M. Barón, I. Kallfass","doi":"10.1109/CASE49439.2021.9551614","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551614","url":null,"abstract":"In power electronic applications, transistors are a vital component. They are, however, susceptible to failures due to degradation of the interconnections and the chip itself. This paper presents a non-destructive approach for failure detection and location in power electronic devices using time-domain reflectometry. The proposed measurement and data generation method is applied to a silicon-carbide power transistor where several characteristics (R, L, C, open, short) and the location of the failure is simulated and characterized. Moreover, the method is also used to find the intrinsic properties of the transistor such as parasitic inductance and capacitance. The data generated is mapped to physical equations, however, the reflected signal of the time-domain reflectometry can be noisy due to multiple discontinuities in the transmission path. Therefore, the simulation and measurement data can be used to train hybrid machine learning models for parameter extraction which automates the failure analysis in Industry4.0 processes to ensure a smart and reliable manufacturing process.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125185375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Function-on-Function Regression for Trajectory Prediction of Small-Scale Particles towards Next-generation Neuromorphic Computing 面向下一代神经形态计算的小尺度粒子轨迹预测的函数对函数回归

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551532

A. Joseph, Juan Wu, Kaiyan Yu, Lan Jiang, N. Cady, Bing Si

{"title":"Function-on-Function Regression for Trajectory Prediction of Small-Scale Particles towards Next-generation Neuromorphic Computing","authors":"A. Joseph, Juan Wu, Kaiyan Yu, Lan Jiang, N. Cady, Bing Si","doi":"10.1109/CASE49439.2021.9551532","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551532","url":null,"abstract":"Precise and efficient motion prediction and manipulation of micro- and nanoparticles in a complex fluid suspension system under external electric fields has the potential to revolutionize the manufacture of scalable functional nanodevices. However, the physical motion model of the particle based on physical simulation does not consider the effects in the complex fluid suspension system, e.g., boundary conditions, fluid motion, and particle interactions, and often results in imperfect prediction of particle trajectories under the coupled global field. This study proposes a data-driven approach for small-scale particle trajectory prediction by leveraging both physical simulation model and experimental data. Historical function-on-function regression is used to predict experimental trajectories from corresponding simulation trajectories. A gradient boosting algorithm is used for model estimation. Our study is the first-of-its-kind that uses historical function-on-function regression to demonstrate the efficacy of predicting experimental trajectories from simulation trajectories in small-scale particle manipulation under electrical fields, which eventually leads to the design of new automated processes for efficient and smart manufacturing of functional nanodevices towards next-generation neuromorphic computing.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123694546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Transformer Based Spatial-Temporal Fusion Network for Metro Passenger Flow Forecasting 基于变压器时空融合网络的地铁客流预测

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551442

Weiqi Zhang, Chen Zhang, F. Tsung

{"title":"Transformer Based Spatial-Temporal Fusion Network for Metro Passenger Flow Forecasting","authors":"Weiqi Zhang, Chen Zhang, F. Tsung","doi":"10.1109/CASE49439.2021.9551442","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551442","url":null,"abstract":"Passenger flow forecasting is a very critical task for the daily operations of metro system. The rapid development of deep learning methods offers us an opportunity to give an end-to-end solution to system-level prediction. However, complex spatial-temporal correlations of passenger flow data makes it quite challenging. Existing studies tend to model spatial and temporal correlations separately, which may lead to information loss and unsatisfactory prediction performance. Meanwhile, they cannot take full advantage of human knowledge and external information, such as geographical information, metro map information, etc, for modeling. To bridge the research gap, in this study, we propose a well-designed transformer based spatial-temporal fusion network (TSTFN). To cooperate with different types of external information and give additional insights, we first use multiple pre-defined graph structures to construct multi-view GCN for spatial dependence modeling. Then we propose a novel spatial-temporal synchronous self-attention layer to model spatial and temporal correlation simultaneously. Experiments show TSTFN outperforms other state-of-the-art deep learning based methods on both long-term and short-term tasks. The effectiveness of its crucial components has also been verified by using ablation study and analysis.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121595858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2