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Concept for Virtual Safety Training System for Human-Robot Collaboration

Procedia Manufacturing 2020年 51卷 54-60页

作者： Morteza Dianatfar Jyrki Latokartano Minna Lanz Automation Technology and Mechanical Engineering Unit Tampere University Tampere Finland

The emergence of Human-Robot Collaboration (HRC) creates the opportunity for operators and robots to work in a shared workspace. Adaptation of such a concept in the field of manufacturing industry aims to increase the flexibility of factory lines and optimize the efficiency of resources. However, employing industrial robots with high speed and enormous forces forms various strains. The major setback is the safety of operators, which demands detailed investigation. Additionally, companies have attempted to create solution-based products to enhance safety in a shared workspace. These solutions require maintaining known-how knowledge regarding usability. Formerly, operators accomplish training for educating themselves upon the assembly process. Training operators lead to diminishing the rate of injury and product cycle time, as well as raising performance and quality. The virtual environment provides a means for operators to experience immersive environments to perceive reality confrontation in a virtual world. Training in these environments empowers operators to recognize safety concerns and instructions. The objective of this study is to propose a concept of virtual safety training in Human-Robot Collaboration.

关键词： Human-Robot Collaboration Virtual Reality Virtual Environment Human Safety

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The application of ultrasonic measurement and machine learning technique to identify flow regime in a bubble column reactor

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Sensors International 2025年第1期6卷 100294-100294页

作者： Wongsaroj, Wongsakorn Thong-Un, Natee Hansot, Jirayut Shoji, Naruki Treenuson, Weerachon Kikura, Hiroshige Department of Instrumentation and Electronics Engineering King Mongkut's University of Technology North Bangkok 1518 Wongsawang Bangsue Bangkok10800 Thailand Center of Excellence on Instrumentation Technology and Automation King Mongkut's University North Bangkok Prachinburi Campus 129 Noenhom MuangPrachinburi25230 Thailand Robotics and Mechanical Engineering Research Unit Muroran Institute of Technology 27-1 Mizumoto-cho MuroranHokkaido050-0071 Japan Office of Atoms for Peace Ministry of Science and Technology 2-12-1 Ookayama Meguro-ku Tokyo152-8550 Japan Laboratory for Zero-Carbon Energy Tokyo Institute of Technology 2-12-1 Ookayama Meguro Tokyo152-8550 Japan

This paper presents a novel technique to classify the flow regimes in bubble columns. The ultrasonic velocity profiler is employed to detect the velocity deviation and echo characteristic of bubbles rising in the column. This information is set as attribute data for the machine learning algorithm. Classification-based machine learning is utilized to classify the flow regimes: bubbly, transition, and churn turbulent, which are defined as categories of the algorithm. Several classifiers were applied in this work, such as K-nearest neighbors, Decision tree, Support vector machines, Naive bayes, and Logical regression. The experimental demonstration was conducted to verify the performance of the proposed technique. Three kinds of two-phase flow with stagnant liquid that had various viscosities were used for the experiment. The air within the superficial velocity range was injected to alter the flow regime. The flow regime classification model was set. The proposed method was applicable to identify the flow regimes. The classifiers were tested, and their accuracy was evaluated. © 2024 The Authors

关键词： Adversarial machine learning

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Coordination concepts for interactions between energy communities, markets, and distribution grids

Coordination concepts for interactions between energy commun...

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CIRED 2021 - The 26th International Conference and Exhibition on Electricity Distribution

作者： S. Repo M. Attar A. Supponen A. Keski-Koukkari A. Safdarian A. Kulmala M. Vilkko Tampere University Unit of Electrical Engineering Tampere Finland VTT Technical Research Centre of Finland Espoo Finland Tampere University Unit of Automation Technology and Mechanical Engineering Tampere Finland

The paper summarizes the qualitative analysis of stakeholder interactions and coordination concepts in respect to four major congestion management solutions of distribution system operators. Benefits and drawbacks of congestion management solutions and interactions are analysed from holistic system perspective and concluded to understand the overall state-of-the-art and development needs. The key result of the analysis is that the winning approach for DSO CM includes all four CM solutions, and the next step is to incorporate technical active network management as novel operation tools for congestion management.

关键词： power transmission economics power system management power markets distribution networks smart power grids

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Improving worker health and safety in wire arc additive manufacturing: A graph-based approach

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Procedia CIRP 2020年 90卷 461-466页

作者： Hari P.N. Nagarajan Suraj Panicker Hossein Mokhtarian Eric Coatanéa Karl R. Haapala Faculty of Engineering and Natural Sciences Automation Technology and Mechanical Engineering Unit Tampere University Tampere 33720 Finland School of Mechanical Industrial and Manufacturing Engineering Oregon State University Corvallis OR 97331 USA

Research on human health and safety impacts of wire arc additive manufacturing is often overshadowed by the need for weld quality and mechanical strength improvements. To address this gap, a review of research literature is conducted focusing on the influence of welding process parameters, welding fumes, and fume exposure on worker health. The review uses a causal graph to classify research literature into two domains: manufacturing technology and public health. The graph serves as a precursor to development of a Bayesian network model, whose expected benefits, steps for implementation, and likely challenges that would be encountered during implementation are discussed.

关键词： Additive manufacturing Welding Safety Bayesian networks

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Composite nonlinear feedback control of a JIB trolley of a tower cranebehaviors 18

Composite nonlinear feedback control of a JIB trolley of a t...

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18th European Control Conference, ECC 2019

作者： Pyrhonen, Veli-Pekka Vilkko, Matti K. Unit of Automation Technology and Mechanical Engineering Tampere University Korkeakoulunkatu 6 Tampere33720 Finland

ISBN: (纸本)9783907144008

Cranes are required to lift and carry loads swiftly to desired positions without causing excessive swaying motion of the load. These are conflicting requirements, which make feedback control of crane systems challenging. Furthermore, variations in rope length and load mass complicate controller design, since they significantly influence swaying dynamics. This paper considers automatic control of Quanser 3DOF tower crane system using composite nonlinear feedback (CNF) methodology. To be more specific, a CNF controller is designed for the jib trolley position of the crane using partial state measurements. The performance of the CNF controller is compared with Quanser's built-in linear quadratic regulator (LQR) controller both in simulation and experimental setups. The results show that the CNF controller provides better load handling capability in terms of fast positioning of the jib trolley and damping of load swaying. © 2019 EUCA.

关键词： Controllers

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Josephson junction based on high critical-temperature superconductors: analysis, microcontroller implementation, and suppression of coexisting and chaotic attractors

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The European Physical Journal B 2022年第9期95卷 1-13页

作者： Ngongiah, Isidore Komofor Ramakrishnan, Balamurali Natiq, Hayder Pone, Justin Roger Mboupda Kuiate, Gaetan Fautso Department of Physics Faculty of Science University of Bamenda Bamenda Cameroon Center for Nonlinear Systems Chennai Institute of Technology Chennai India Information Technology College Imam Ja’afar Al-Sadiq University Baghdad Iraq Research Unit of Automation and Applied Computer (RUAIA) Electrical Engineering Department of IUT-FV University of Dschang Bandjoun Cameroon Department of Physics Higher Teacher Training College University of Bamenda Bamenda Cameroon Department of Mechanical and Industrial Engineering National Higher Polytechnic Institute University of Bamenda Bamenda Cameroon

A Josephson junction (JJ) based on high critical-temperature superconductors described by a linear resistive–capacitive–inductance shunted junction (LRCLSJ) model with unharmonic current-phase relation (UCPR) is theoretically and experimentally investigated in this paper. The numerical simulations indicate that JJ based on high critical-temperature superconductors exhibits excitable mode, regular spiking, periodic bursting, relaxation oscillations, chaotic attractors, and coexisting attractors. The theoretical investigations are verified experimentally through the microcontroller implementation. In addition, the coexistence between chaotic and limit cycle attractors found in JJ based on high critical-temperature superconductors is controlled to the desired trajectory using the linear augmentation control method. Finally, analytical calculations and numerical simulations are carried out to show the serviceableness of the two designed single controllers in suppressing chaos in JJ based on high critical-temperature superconductors.

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Data-Driven Distributed Algorithms for Estimating Eigenvalues and Eigenvectors of Interconnected Dynamical Systems

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IFAC-PapersOnLine 2020年第2期53卷 52-57页

作者： Azwirman Gusrialdi Zhihua Qu Automation Technology and Mechanical Engineering Unit Faculty of Engineering and Natural Sciences Tampere University Tampere 33014 Finland Department of Electrical and Computer Engineering University of Central Florida Orlando 32816 USA

The paper presents data-driven algorithms to estimate in a distributed manner the eigenvalues, right and left eigenvectors of an unknown linear (or linearized) interconnected dynamic system. In particular, the proposed algorithms do not require the identification of the system model in advance before performing the estimation. As a first step, we consider interconnected dynamical system with distinct eigenvalues. The proposed strategy first estimates the eigenvalues using the well-known Prony method. The right and left eigenvectors are then estimated by solving distributively a set of linear equations. One important feature of the proposed algorithms is that the topology of communication network used to perform the distributed estimation can be chosen arbitrarily, given that it is connected, and is also independent of the structure or sparsity of the system (state) matrix. The proposed distributed algorithms are demonstrated via a numerical example.

关键词： distributed estimation data-driven algorithm eigenvalues eigenvectors

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Virtual Teaching for Assembly Tasks Planning

Virtual Teaching for Assembly Tasks Planning

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IEEE International Conference on Human-Machine Systems

作者： Alexandre Angleraud Robert Codd-Downey Metodi Netzev Quentin Houbre Roel Pieters Unit of Automation Technology and Mechanical Engineering Tampere University Tampere Finland Department of Electrical Engineering and Computer Science York University Toronto Canada

ISBN: (数字)9781728158716

ISBN: (纸本)9781728158723

Small and Medium-size Enterprises require increasingly versatile robots that are capable of learning new skills during their operating life span, in addition to the ability to integrate themselves into human teams as a new and effective partner. Teaching information and skills to a robot can quickly become very complex, especially when considering that the human partner of the robot is inexperienced in the field and does not have access to intuitive interaction channels to train such robots. In this work, a system is proposed that can virtually define an assembly task, based on CAD modelling that describe constraints between assembly parts. These constraints are then extracted in an ontology which is automatically translated into Simple Temporal Networks (STNs) leading to joint action *** show the automatic translation between virtual teaching and knowledge acquired by the robot on a peg-in-hole problem before illustrating the connection to planning for human-robot collaborative tasks. As a proof of concept, these developments demonstrate that a CAD guided assembly planner can circumvent the need for skilled robot programming.

关键词： Task analysis Robots Solid modeling Planning Ontologies Collaboration Semantics

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Fault detection of elevator system using profile extraction and deep autoencoder feature extraction 33

Fault detection of elevator system using profile extraction ...

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33rd Annual European Simulation and Modelling Conference, ESM 2019

作者： Mishra, Krishna Mohan Saxen, John-Eric Bjorkqvist, Jerker Huhtala, Kalevi J. Unit of Automation Technology and Mechanical Engineering Tampere University Tampere Finland Department of Information Sciences Abo Akademi University Turku Finland

ISBN: (纸本)9789492859099

In this paper, we propose a new algorithm for data extraction from time series data, and furthermore automatic calculation of highly informative deep features to be used in fault detection. In data extraction elevator start and stop events are extracted from sensor data, and a generic deep autoencoder model is also developed for automated feature extraction from the extracted profiles. After this, extracted deep features are classified with random forest algorithm for fault detection. Sensor data are labelled as healthy and faulty based on the maintenance actions recorded. The rest of the healthy data are used for validation of the model to prove its efficacy in terms of avoiding false positives. We have achieved nearly 100% accuracy in fault detection along with avoiding false positives based on new extracted deep features, which outperforms results using existing features. Existing features are also classified with random forest to compare results. Our developed algorithm provides better results due to the new deep features extracted from the dataset when compared to existing features. This research will help various predictive maintenance systems to detect false alarms, which will in turn reduce unnecessary visits of service technicians to installation sites. Copyright © 2019 EUROSIS-ETI.

关键词： Feature extraction

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M-Estimator Application in Real-Time Sensor Fusion for Smooth Position Feedback of Heavy-Duty Field Robots

M-Estimator Application in Real-Time Sensor Fusion for Smoot...

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IEEE Conference on Cybernetics and Intelligent Systems

作者： Henri Liikanen Mohammad M. Aref Jouni Mattila Unit of Automation Technology and Mechanical Engineering Tampere University Tampere Finland

ISBN: (数字)9781728134581

ISBN: (纸本)9781728134598

In this paper, we study the performance of a complementary filter with adaptive weights in a sensor fusion application for real-time localization of an omnidirectional field robot. The test-case robot is a large, four-wheel drive and steer (4WDS) construction vehicle with nonlinear internal dynamics and hydraulic driving and steering actuators. Our objective is to provide the vehicle's real-time controller with robust, smooth feedback that prevents unnecessary oscillations in steering, which can waste significant amounts of energy. We do so by assigning weights for measurements based on their consistency with the robot's motions. The calculations are based on two main data sources: (1) measured velocity vectors from wheel driving (odometer) and steering of the 4WDS test-case robot; and (2) data obtained from a differential global navigation satellite system on the absolute pose of the robot. We show that the sensor fusion is robust to the noise and single point failures of the sensors, while the maximum heading oscillations are reduced by 70%-95%, preserving the accuracy of the global positioning system. Moreover, we demonstrate the feasibility and efficacy of the real-time implementation of this filtering method in path-following control of the robot.

关键词： Two dimensional displays Conferences Cybernetics Intelligent systems Robots automation Mechatronics

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