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international conference on Control, automation, robotics and Vision

作者： Xiao Wang Shandong Vocational College of Light Industry Zibo China

Soft sensors have been widely used in industrial processes in the past two decades, using easy-to-measure process variables to predict hard-to-measure ones. Sufficient training data can significantly improve the prediction performance as well as speed up the computation with low cost in the modeling process of the soft sensor. However, data collection is often difficult due to the harsh environment of the industrial process. Generative adversarial networks (GANs) is a prominent method for learning generative models in recent years. In this paper, a generative model named DWGAN based on improved Wasserstein generative adversarial networks (WGAN) is proposed to generate new samples for soft sensors. For evaluating the proposed method, a practical industrial experiment is studied in the case of paucity of data, and three other state-of-the-art generative models are adopted for comparison. the experimental results show that the samples yielded by the proposed method behave more similarly with the real samples compared to samples provided by other methods. Additionally, these synthetic samples can make the training data sufficient and significantly improve the prediction accuracy of the soft sensors.

关键词： Training Gallium nitride Generators Computational modeling Generative adversarial networks Robot sensing systems Data models

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Simplified Modeling Approach to Characterize Sudden Load Disturbances in WirelessHART FOPDT Systems

Simplified Modeling Approach to Characterize Sudden Load Dis...

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international conference on Control, automation, robotics and Vision (ICARCV)

作者： Napasool Wongvanich Puntani Pongsumpun Department of Instrumentation and Control Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Mathematics King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

this paper presents the simplified modelling approach to characterize sudden load disturbance in WirelessHART™. Two approaches are presented. the model was firstly formulated through Laplace transformation, where the resulting integral equation renders non-linear optimization problems into simple linear optimizations. Experiments were conducted on a coupled tanks system connected through the WirelessHART™ protocol. Based on the initial fit to the experimental results, the second model then places two locally affine relationships, one for the load flow disturbances, and the other for the level measurements to the responses. the extended locally affine model gave on average a 25% reduction in errors, compared to the Laplace-based method, while better captured the non-linear effects resulting from the WirelessHART™.

关键词： Mathematical model Load modeling Data models Integral equations Protocols Level measurement Delays

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A Review on Short-Term Electricity Price Forecasting Techniques for Energy Markets

A Review on Short-Term Electricity Price Forecasting Techniq...

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international conference on Control, automation, robotics and Vision

作者： LianLian Jiang Guoqiang Hu A*STAR Institute for Infocomm Research Singapore School of Electrical and Electronic Engineering Nanyang Technological University Singapore

the electricity price forecasting (EPF) is essential for decision-making mechanisms of market participants to survive in the deregulated and competing commercial environment. Due to special features of the electricity such as seasonality, the constant balance between production and consumption required by the system, and environmental dependencies, electricity prices generally shows extreme volatility and price spikes with the heteroscedasticity. this paper provides a survey of main EPF methodologies and the ultimate goal of this survey is to provide readers insights and guidelines for choosing different EPF techniques for day-ahead electricity markets. For each type of method, we briefly introduce its principle and then describe how it is applied in EPF. Many new EPF techniques developed recently are also discussed, especially the artificial intelligence forecasting methods. the pros and cons of each type of method are provided in a final table so that users can pay attention to when choosing them. In the final section, several promising methods and potential directions for further exploration are presented.

关键词： Electricity price forecasting (EPF) deep learning artificial intelligence energy market time series models

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Model-Based Development of Robotic Systems and Services in Construction robotics 25th

Model-Based Development of Robotic Systems and Services in C...

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25th international conference on robotics in Alpe-Adria-Danube Region (RAAD)

作者： Schlette, Christian Rossmann, Juergen Rhein Westfal TH Aachen Inst Man Machine Interact MMI Aachen Germany

ISBN: (纸本)9783319490588;9783319490571

More and more of our indoor/outdoor environments are available as 3D digital models. In particular, digital models such as the CityGML (City Geography Markup Language) format for cities and the BIM (Building Information Modeling) methodology for buildings are becoming important standards for project management in the construction industry. In this contribution, we are proposing the combination of existing city and building models with methods from 3D simulation and 3D simulation-based system control in order to provide comprehensive geometries and semantics for the representation of large-scale working environments. In Virtual Testbeds for construction robotics, such large-scale working environments can then be systematically accessed as mental models for the model-respectively 3D simulation-based development and control of robotic systems and services.

关键词： Construction robotics Model-Based development CityGML BIM

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TOPIC-GUIDED ATTENTION FOR IMAGE CAPTIONING

TOPIC-GUIDED ATTENTION FOR IMAGE CAPTIONING

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IEEE international conference on Image Processing

作者： Zhihao Zhu Zhan Xue Zejian Yuan Institute of Artificial Intelligence and Robotics Xian Jiaotong University P. R. China

Attention mechanisms have attracted considerable interest in image captioning because of its powerful performance. Existing attention-based models use feedback information from the caption generator as guidance to determine which of the image features should be attended to. A common defect of these attention generation methods is that they lack a higher-level guiding information from the image itself, which sets a limit on selecting the most informative image features. therefore, in this paper, we propose a novel attention mechanism, called topic-guided attention, which integrates image topics in the attention model as a guiding information to help select the most important image features. Moreover, we extract image features and image topics with separate networks, which can be fine-tuned jointly in an end-to-end manner during training. the experimental results on the benchmark Microsoft COCO dataset show that our method yields state-of-art performance on various quantitative metrics.

关键词： Visualization Semantics Feature extraction Training Decoding Generators Measurement

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Using FEM simulations of cutting for evaluating the performance of different johnson cook parameter sets acquired with inverse methods

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robotics AND COMPUTER-INTEGRATED MANUFACTURING 2017年 47卷 95-101页

作者： Laakso, Sampsa V. A. Niemi, Esko Aalto Univ Sch Engn Dept Engn Design & Prod Espoo 02150 Southern Finlan Finland

Material model parameters are the primary source of error in the finite element analysis (FEM) of cutting processes. Expensive and time consuming material testing is required in order to describe the material's behavior in high temperature and high strain rate conditions during cutting. An alternative approach has been suggested in research papers;inverse analysis using cutting experiments together with FE analysis or analytical models. the latest approach is to combine an analytical model together with a material model capable of describing flow stress in terms of strain, strain rate and temperature, and using cutting experiments to acquire input parameters for inverse analysis, from which the material model parameters can be solved. In this paper, performance evaluation is done for five different sets of Johnson Cook parameters for AISI 1045, acquired with materials testing, inverse analysis with FEM, and the proposed combined inverse analysis with an analytical model and cutting experiments. the performance is evaluated by running simulations with a wide range of cutting parameters and comparing the simulated results of cutting forces and temperature to known experimental results found in literature. It was found that the proposed inverse method produces better performing model parameters than those found in literature.

关键词： Cutting FEM Johnson-Cook Model Inverse Analysis AISI 1045

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Reasonable Grasping Based on Hierarchical Decomposition models of Unknown Objects

Reasonable Grasping Based on Hierarchical Decomposition Mode...

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international conference on Control, automation, robotics and Vision

作者： Chongkun Xia Yunzhou Zhang Yanli Shang Tongbo Liu College of Information Science and Engineering Northeastern University Shenyang CHN School of Computer & Communication Engineering University of Science & Technology of Beijing Beijing CHN

Reasonable grasping for unknown objects is an interesting and important problem for autonomous robots in unstructured environment. Current grasping methods for unknown objects mostly focus on precision and stability. Until now there are few specific studies or reports describing reasonable grasp of unknown objects for service robots such as home service robots and nursing robots. In the paper we proposed a reasonable grasping method for unknown objects based on hierarchical decomposition point cloud models using a vision sensor. As a complex task, vision-based grasp is composed of a series solution of a mixture of subproblems. therefore, we adopt an improved superquadrics fitting algorithm with the improved cuckoo search strategy (S-ICS) to achieve restoration and segmentation of incomplete point cloud data of unknown objects in a single visual angle. then a reasonable region decision method based on hierarchical decomposition models is proposed to evaluate the reasonableness of grasped positions of unknown objects. Finally, we use a simulation to verify the effectiveness of the proposed method. Moreover, we also perform an extensive real-world grasping experiment on a set of unknown objects in daily use. the results also verify the effectiveness of our approach.

关键词： Grasping three-dimensional displays Pose estimation Service robots Linear programming Strain

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Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping

Using Simulation and Domain Adaptation to Improve Efficiency...

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IEEE international conference on robotics and automation

作者： Konstantinos Bousmalis Alex Irpan Paul Wohlhart Yunfei Bai Matthew Kelcey Mrinal Kalakrishnan Laura Downs Julian Ibarz Peter Pastor Kurt Konolige Sergey Levine Vincent Vanhoucke Google Brain X

Instrumenting and collecting annotated visual grasping datasets to train modern machine learning algorithms can be extremely time-consuming and expensive. An appealing alternative is to use off-the-shelf simulators to render synthetic data for which ground-truth annotations are generated automatically. Unfortunately, models trained purely on simulated data often fail to generalize to the real world. We study how randomized simulated environments and domain adaptation methods can be extended to train a grasping system to grasp novel objects from raw monocular RGB images. We extensively evaluate our approaches with a total of more than 25,000 physical test grasps, studying a range of simulation conditions and domain adaptation methods, including a novel extension of pixel-level domain adaptation that we term the GraspGAN. We show that, by using synthetic data and domain adaptation, we are able to reduce the number of real-world samples needed to achieve a given level of performance by up to 50 times, using only randomly generated simulated objects. We also show that by using only unlabeled real-world data and our GraspGAN methodology, we obtain real-world grasping performance without any real-world labels that is similar to that achieved with 939,777 labeled real-world samples.

关键词： Grasping Robots Training Feature extraction Adaptation models Cameras Task analysis

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Motion Recognition System for Worker Safety in Manufacturing Work Cell

Motion Recognition System for Worker Safety in Manufacturing...

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international conference on Control, automation and Systems

作者： Sangseung Kang Kyekyung Kim Intelligent Robotics Research Division ETRI Daejeon Korea

ISBN: (纸本)9781538670804;9788993215168

With a paradigm shift of the manufacturing process into an active module process system, an increasing demand for a lightweight and safe manufacturing environment has developed. To share a workspace between a worker and robot in a manufacturing work cell, technical methods ensuring the safety of the worker must be provided. In this paper, we propose a vision-based worker safety system for enabling a safe operation even when the worker of a manufacturing process shares a workspace with a robot. the proposed system monitors the position of the worker based on a vision system and supports the worker safety by avoiding collisions with the robot according to the workspace classification. the system also recognizes dangerous movements of the worker, and provides safety services through interactions with the manufacturing robot by matching predefined motion models.

关键词： Manufacturing robot Collaborative operation Worker safety Motion recognition

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Energy-optimal layout design of robotic work cells: Potential assessment on an industrial case study

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robotics AND COMPUTER-INTEGRATED MANUFACTURING 2017年 47卷 102-111页

作者： Gadaleta, Michele Berselli, Giovanni Pellicciari, Marcello Univ Modena & Reggio Emilia Dept Engn Enzo Ferrari I-41125 Modena Italy Univ Genoa Dept Mech Engn Energy Managment & Transportat I-16145 Genoa Italy

this paper presents a new method for optimizing the layout position of several Industrial Robots (IRs) placed within manufacturing work-cells, in order to execute a set of specified tasks with the minimum energy consumption. At first, a mechatronic model of an anthropomorphous IR is developed, by leveraging on the Modelica/Dymola built-in capabilities. the IR sub-system components (namely mechanical structure, actuators, power electronic and control logics) are modeled with the level of detail strictly necessary for an accurate prediction of the system power consumption, while assuring efficient computational efforts. Secondly, once each IR task is assigned, the optimal work-cell layout is computed by using proper optimization techniques, which numerically retrieve the IR base position corresponding to the minimum energy consumption. As an output to this second development stage, a set of color/contour maps is provided, that depicts both energy demand and time required for the task completion as function of the robot position in the cell to support the designer in the development of an energy-efficient layout. At last, two robotic manufacturing work-cells are set-up within the Delmia robotics environment, in order to provide a benchmark case study for the evaluation of any energy saving potential. Numerical results confirm possible savings up to 20% with respect to state-of-the-art work-cell design practice.

关键词： Industrial robots Energy conservation Mechatronics Prediction models Numerical analysis

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