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Airfoil Inverse Design using Conditional Generative Adversarial Networks

Airfoil Inverse Design using Conditional Generative Adversar...

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

作者： Xavier Tan Dai Manna Joyjit Chattoraj Liu Yong Xu Xinxing Dao My Ha Yang Feng Computing & Intelligence Department Institute of High Performance Computing A*STAR Singapore School of Informatics & IT Diploma in Big Data Analytics Temasek Polytechnic Singapore Fluid Dynamics Department Institute of High Performance Computing A*STAR Singapore

ISBN: (纸本)9781665476881

Creating an aerodynamic shape, like an airfoil wing, requires many factors to be considered, especially aerodynamic properties such as its lift-to-drag ratio (L/D). Currently, generating feasible airfoil shapes usually requires computationally expensive tools, such as Computational Fluid Dynamics (CFD). In recent years, increasing work has been directed to utilizing machine learning algorithms to synthesize accurate airfoil shapes while reducing the required computational cost. Generative Adversarial Network (GAN) is one of many algorithms to see success in airfoil shape optimization and is shown to generate good airfoils given a small set of training examples. This paper focuses on implementing a conditional GAN (cGAN) based framework with various filters for airfoil inverse design problem. By labelling the training dataset with aerodynamic characteristics separated by pre-defined thresholds to lift-to-drag ratio (L/D) and shape area, the class labels will be able to guide the network to generate different classes of airfoils influenced by these characteristics. Together with layers of Savitzky-Golay (SG) filter and B-Spline Interpolation, the developed model was shown to achieve good performance in generating new airfoils. In addition, we explored the viability of adding Wasserstein loss from Wasserstein GAN into the network architecture, forming a cWGAN-GP. Testing results showed that cWGAN-GP was able to achieve better performance for a specific airfoil class.

关键词： Training Interpolation Machine learning algorithms Shape Atmospheric modeling Computational fluid dynamics Generative adversarial networks

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Interval-based Sound Source Mapping for Mobile Robots 17

Interval-based Sound Source Mapping for Mobile Robots

引用

17th international conference on informatics in control, automation and robotics (ICINCO)

作者： Rauschenberger, Axel Wagner, Bernardo Leibniz Univ Hannover Inst Syst Engn Real Time Syst Grp RTS Appelstr 9A D-30167 Hannover Germany

ISBN: (纸本)9789897584428

Auditory information can expand the knowledge of the environment of a mobile robot. Therefore, assigning sound sources to a global map is an important task. In this paper, we first form a relationship between the microphone positions and auditory features extracted from the microphone signals to describe the 3D position of multiple static sound sources. Next, we form a Constraint Satisfaction Problem (CSP), which links all observations from different measurement positions. Classical approaches approximate these non-linear system of equations and require a good initial guess. In contrast, in this work, we solve these equations by using interval analysis in less computational effort. This enables the calculation being performed on the hardware of a robot at run time. Next, we extend the approach to model uncertainties of the microphone positions and the auditory features extracted by the microphones making the approach more robust in real applications. Last, we demonstrate the functionality of our approach by using simulated and real data.

关键词： Mobile robotics Sound Source Mapping Robot Audition Interval Analysis

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Automatic Domain Extension and Optimization Based on Set-Theory 17th

Automatic Domain Extension and Optimization Based on Set-T...

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17th international conference on informatics in control, automation and robotics, ICINCO 2020

作者： Kast, Bernd Dietrich, Vincent Albrecht, Sebastian von Wichert, Georg Feiten, Wendelin Zhang, Jianwei Siemens AG Corporate Technology Otto-Hahn-Ring 6 Munich81739 Germany Faculty of Mathematics Informatics and Natural Sciences University of Hamburg Vogt-Kölln-Str. 30 Hamburg22527 Germany

ISBN: (纸本)9783030924416

Autonomous machines promise more flexibility and robustness changes in their environment compared to manually programmed solutions in industrial applications. However, the autonomous planning of actions involves discrete as well as continuous properties, which results in a np-hard planning problem. Especially for multiple machines and long planning horizons the design of domains requires a lot of fine tuning and thus manual effort. Modularization and reuse of existing domain knowledge with formalized models is one solution to this issue. However, the models of different projects tend to be misaligned, in particular when several parties contributed to the project, which deteriorates the performance. In this paper, we present two domain optimization and extension algorithms, which adapt the models to facilitate planning. The first algorithm handles inconsistent units, or even misaligned pieces of sub-information. It automatically generates conversions and allows to call operations with a wider range of input types. The second algorithm aligns models from different sources with varying modeling views. After this reformulation, we can compose models more efficiently to a larger domain. For both optimizations, we rely on the formal set-based models that we also use in our previously presented hierarchical planning algorithm. Our hierarchical approach allows an almost linear scalability with the length of the plan. However, it comes with non-optimality effects due to the imposed intermediate goals that depend on the quality of the model. The optimization algorithms of this paper allow to adapt and extend the model so that valid shortcuts reduce these suboptimalities. We conduct experiments on a task and motion assembly problem, demonstrating scalability for up to 62 parts and plans with over 1000 steps, which either result in discrete state or high-level position changes, with planning times of less than 15 min. Our experiments also include the successful plan execution o

关键词： Scalability

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Utilization of IMU-Based Gesture Recognition in the Treatment of Diabetes

Utilization of IMU-Based Gesture Recognition in the Treatmen...

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IEEE international conference on automation, Quality and Testing, robotics, AQTR

作者： Marcell Szá ntó Gergő Strasser Lá szló Szá sz Lehel Dé nes-Fazakas Gyö rgy Eigner Gá bor Kerté sz Levente Ková cs Physiological Controls Research Center &#x00D3 buda University Budap&#x00E9 st Software Engineering Institute John von Neumann Faculty of Informatics &#x00D3 buda University Budapest Biomatics and Applied Artificial Intelligence Institute John von Neumann Faculty of Informatics &#x00D3 Applied Informatics and Applied Mathematics Doctoral School &#x00D3 E&#x00F6 tv&#x00F6 s L&#x00F3 r&#x00E1 nd Research Network Institute for Computer Science and Control Budapest Hungary

ISBN: (数字)9781665479332

ISBN: (纸本)9781665479349

Changes in blood sugar levels are significantly affected by dietary carbohydrate intake, which clearly affects insulin therapy. However, currently available insulin pumps do not perform continuous blood glucose monitoring, and the patient should do so. The quality of the treatment can be further improved if the phenomenon of eating can be recognized based on the characteristic movements, and then by sending an automatic signal of the event to the insulin pump, it can be taken into account that an increase in blood sugar levels is expected. In our work, we focused on this task and, using 4 different tools, collected data from more than 8 people on their hand movements during their meals, on which we performed various data manipulations. Finally, using the aggregation of the obtained data set, we tested different machine learning techniques, from which we will select the optimal algorithm that can recognize the motion characteristic of carbohydrate intake independently of the person with the smallest error. The article presents the tools used for the measurement, the operations performed on the data, as well as the tried and tested machine learning methods and their comparative analysis. Our goal is to improve the quality of life of people with diabetes by increasing the effectiveness of base bolus therapy.

关键词： Medical treatment Insulin pumps Gesture recognition Data collection Diabetes Character recognition Biosensors

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Preliminary study of AR navigation-guided core-needle breast biopsy

Preliminary study of AR navigation-guided core-needle breast...

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international conference on control, automation and Systems ( ICCAS)

作者： Nova Eka Diana Jegyeong Ryu Hee Ryung Lee O Youngseok Deukhee Lee Division of AI-Robotics KIST School University of Science and Technology Seoul Republic of Korea Center for Healthcare Robotics Korea Institute of Science and Technology Seoul Republic of Korea Department of Informatics Universitas YARSI Jakarta Indonesia Division of electrical and electronic engineering Yonsei University Seoul Republic of Korea Yonsei-KIST Convergence Research Institute Yonsei University Seoul Republic of Korea

Accurate tumor localization has remained to be one of the biggest challenges in core-needle biopsy due to the malleability and texture-heterogeneity of tissues surrounding a tumor. To overcome these limitations, we explored the effectiveness of augmented reality (AR)-guidance to navigate the core-needle insertion in breast biopsy thanks to the enhanced technology of AR. Our proposed framework consists of two independent functions: tumor localization and needle pose tracking in real-time. First, tumor localization was achieved by employing the two-front environmental sensors of HoloLens 2 (HL2) for tracking the passive-reflective markers. Given the geometrical information of the reference markers, the stereo-correspondences and the marker pose can be calculated efficiently for overlaying the corresponding virtual models in HL2. Second, an external RGB camera was used to track the pose of a needle. A You-Only-Look-Once (YOLO) model with a customized training set of 200 images was employed to detect the collinear pinktape points attached to the needle. The interpoint-distance between these points will be utilized to estimate the pose of a needle that will be sent to HL2 using TCP/IP communication. Finally, real-time navigation of needle insertion can be rendered in HL2 using a more accurate transformation to assist the breast biopsy. Overall, the preliminary results demonstrate that the whole process can be executed in a reasonable running time of less than two seconds.

关键词： Location awareness Training Navigation Breast biopsy TCPIP Needles control systems

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Unified Push Recovery Fundamentals: Inspiration from Human Study

Unified Push Recovery Fundamentals: Inspiration from Human S...

引用

2020 IEEE international conference on robotics and automation, ICRA 2020

作者： McGreavy, Christopher Yuan, Kai Gordon, Daniel Tan, Kang Wolfslag, Wouter J Vijayakumar, Sethu Li, Zhibin University of Edinburgh Edinburgh Centre for Robotics School of Informatics United Kingdom

ISBN: (纸本)9781728173955

Currently for balance recovery, humans outperform humanoid robots which use hand-designed controllers in terms of the diverse actions. This study aims to close this gap by finding core control principles that are shared across ankle, hip, toe and stepping strategies by formulating experiments to test human balance recoveries and define criteria to quantify the strategy in use. To reveal fundamental principles of balance strategies, our study shows that a minimum jerk controller can accurately replicate comparable human behaviour at the Centre of Mass level. Therefore, we formulate a general Model-Predictive control (MPC) framework to produce recovery motions in any system, including legged machines, where the framework parameters are tuned for time-optimal performance in robotic systems. © 2020 IEEE.

关键词： controllers

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Behavior-Based Obstacle Detection in Off-Road Environments Considering Data Quality 14th

Behavior-Based Obstacle Detection in Off-Road Environments C...

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14th international conference on informatics in control, automation and robotics (ICINCO)

作者： Wolf, Patrick Ropertz, Thorsten Berns, Karsten Univ Kaiserslautern Dept Comp Sci Robot Res Lab Kaiserslautern Germany

ISBN: (纸本)9783030112929;9783030112912

In off-road environments, the assessment and classification in travers-able and non-traversable areas is a challenging task. Not only does the drive-ability depend on the vehicle's state in combination with the environmental geometry, but also the assessment is complicated by noisy and wrong sensor data. Thereby, faulty evaluation may lead to severe harm to goods or people since either safety issues or reliability problems are caused. While for the control part behavior-based systems proved to be suitable due to their inherent robustness against unforeseen situations, robust perception is still an unsolved problem leading to severe system failures. This paper faces the perception problem by introducing a new data quality-based perception module based on the integrated Behavior-Based control (iB2C) architecture. Therefore, a new concept of data quality in behavior-based systems and methods for quality aware data fusion are developed while taking advantage of the modularity, extensibility and traceability of the existing architecture.

关键词： Behavior-based control Quality-based perception Obstacle avoidance Off-road robotics

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A Deep Learning Tool to Solve Localization in Mobile Autonomous robotics 17

A Deep Learning Tool to Solve Localization in Mobile Autonom...

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17th international conference on informatics in control, automation and robotics (ICINCO)

作者： Cebollada, Sergio Paya, Luis Flores, Maria Roman, Vicente Peidro, Adrian Reinoso, Oscar Miguel Hernandez Univ Dept Syst Engn & Automat Elche Spain

ISBN: (纸本)9789897584428

In this work, a deep learning tool is developed and evaluated to carry out the visual localization task for mobile autonomous robotics. Through deep learning, a convolutional neural network (CNN) is trained with the aim of estimating the room where an image has been captured, within an indoor environment. This CNN is not only used as tool to solve a room estimation, but it is also used to obtain global-appearance descriptors of the input image from its intermediate layers. The localization task is addressed in two different ways: globally, as an image retrieval problem and hierarchically. About the global localization, the position of the robot is estimated by using a nearest neighbour search between the holistic description obtained from a test image and the training dataset (using the CNN to obtain the descriptors). Regarding the hierarchical localization method, first, the CNN is used to solve the rough localization step and after that, it is also used to obtain global-appearance descriptors;second, the robot estimates its position within the selected room through a nearest neighbour search by comparing the obtained holistic descriptor with the visual model contained in that room. Throughout this work, the localization methods are tested with a visual dataset that provides omnidirectional images from indoor environments under real-operation conditions. The results show that the proposed deep learning tool is an efficient solution to carry out visual localization tasks.

关键词： Mobile robotics Omnidirectional Images Holistic Description Deep Learning Hierarchical Localization

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Proceedings of 14th international conference on Electromechanics and robotics “Zavalishin's Readings” 1

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丛书名： Smart Innovation, Systems and Technologies

2020年

作者： Andrey Ronzhin Vladislav Shishlakov

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Development of a Fault Adaptation System for Underwater Robot Manipulators

Development of a Fault Adaptation System for Underwater Robo...

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Ocean Studies (ICOS), international conference on

作者： Vladimir Filaretov Alexander Zuev Alexey Zhirabok Alexander Protsenko Institute of Automation and Control Processes Vladivostok Russia Department of Informatics and Control in Technical Systems Sevastopol State University Sevastopol Russia Institute of Marine Technology Problems Vladivostok Russia Department of Automatics and Robotics Far Eastern Federal University Vladivostok Russia

ISBN: (纸本)9781665473736

The paper describes the development and research of a system of adaptation to faults of manipulators of underwater robots. The following types of faults were considered: unknown additional load torques on the output shafts of the manipulator electric drives, changes in the electrical resistance of the armature windings of electric motors, and measurement errors of sensors of the position of the manipulator links. The proposed system makes it possible to identify these faults and compensate for their negative consequences in two stages. At the first stage, the values of faults are estimated using a bank of diagnostic observers operating in a sliding mode. At the second stage, with the help of the obtained estimates, a control signal is generated that ensures the stabilization of dynamic properties of each electric drive at the desired level. To check the operability of the proposed system, a computer simulation was carried out.

关键词： Fault diagnosis Shafts Resistance Autonomous underwater vehicles Measurement errors Computer simulation Oceans

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