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arXiv 2018年

作者： Tiwari, Kshitij Intelligent Robotics Group Department of Electrical Engg. & Automation Aalto University Espoo02150 Finland

This document serves to complement our website which was developed with the aim of exposing the students to Gaussian Processes (GPs). GPs are non-parametric bayesian regression models that are largely used by statisticians and geospatial data scientists for modeling spatial data. Several open source libraries spanning from Matlab [1], Python [2], R [3] etc. are already available for simple plug-and-use. The objective of this handout and in turn the website was to allow the users to develop stand-alone GPs in Python by relying on minimal external dependencies. To this end, we only use the default python modules and assist the users in developing their own GPs from scratch giving them an in-depth knowledge of what goes on under the hood. The module covers GP inference using maximum likelihood estimation (MLE) and gives examples for 1D (dummy) spatial data. Copyright © 2018, The Authors. All rights reserved.

关键词： Python

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Seam tracking and welding bead geometry analysis for autonomous welding robot 14

Seam tracking and welding bead geometry analysis for autonom...

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14th Latin American robotics Symposium and 5th Brazilian Symposium on robotics, LARS-SBR 2017

作者： Soares, Luciane B. Weis, Átila A. Rodrigues, Ricardo N. Drews, Paulo L. J. Guterres, Bruna Botelho, Silvia S. C. Filho, Nelson D. Intelligent Robotics and Automation Group - Nautec Federal University of Rio Grande - FURG Brazil

ISBN: (纸本)9781538609569

Welding is a process recognized by the laborious work and hazardous work environment it takes place, but it is an important process in different industrial scenarios, like the shipbuilding industry. The use of robots has been increasing in recent years, reducing the human interference necessary for the process. This paper proposes a system for automated seam tracking and a geometric welding bead analysis systems based on passive monocular vision. Using an vision system attached to a linear welding robot, images of the gap between two plates are acquired, during the welding process in order to identify the groove's characteristics and perform a autonomous welding. These characteristics are used during the geometric weld bead analysis to detect geometric failures such as misalignment, lack or excess of fusion, among others. © 2017 IEEE.

关键词： Geometry

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Correction to: Integrating Social Assistive Robots, IoT, Virtual Communities and Smart Objects to Assist at-Home Independently Living Elders: the MoveCare Project

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International Journal of Social robotics 2022年第9期14卷 2045-2045页

作者： Luperto, Matteo Monroy, Javier Renoux, Jennifer Lunardini, Francesca Basilico, Nicola Bulgheroni, Maria Cangelosi, Angelo Cesari, Matteo Cid, Manuel Ianes, Aladar Gonzalez-Jimenez, Javier Kounoudes, Anastasis Mari, David Prisacariu, Victor Savanovic, Arso Ferrante, Simona Borghese, N. Alberto Applied Intelligent System Lab Department of Computer Science University of Milan Milano Italy Machine Perception and Intelligent Robotics Group (MAPIR) Department of System Engineering and Automation University of Malaga and Instituto de Investigación Biomédica de Málaga–IBIMA Malaga Spain Machine Perception and Interaction Lab Örebro University Örebro Sweden NearLab Department of Electronics Information and Bioengineering Politecnico di Milano Milano Italy AB.Acus SRL Milan Italy University of Manchester Manchester UK IRCCS Istituti Clinici Scientifici Maugeri University of Milan Milan Italy Junta de Extremadura Merida Spain Korian Milan Italy SignalGeneriX Limassol Cyprus EURECAT Barcelona Spain University of Oxford Oxford UK Smart Com Ljubjana Slovenia

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The Design and Implementation of Information Management and Control System for Military Products intelligent Assembly Line Based on JIT

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Journal of Physics: Conference Series 2020年第1期1575卷

作者： Yuenan Zhao Jinsong Du Xiang Li Jinhu Hua Qingjun Liu Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang 110016 China Inner Mongolia North Heavy Industries Group Company Ltd. Baotou 014033 China

To enhance the capabilities of advanced military product manufacturing, this paper carries out a new design and implementation of advanced military product assembly line. Through research on the current bottleneck problems and the aims of the production line, the system structure is designed and the function requirements are analysed to complete the software architecture design. Finally, the JIT information management and control system is completed based on information technology and lean manufacturing.

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Safe-To-Explore State Spaces: Ensuring Safe Exploration in Policy Search with Hierarchical Task Optimization

arXiv

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arXiv 2018年

作者： Lundell, Jens Krug, Robert Schaffernicht, Erik Stoyanov, Todor Kyrki, Ville Intelligent Robotics Group Department of Electrical Engineering and Automation Aalto University Finland AASS Research Center Örebro University Sweden Robotics Learning and Perception lab KTH Royal Institute of Technology Sweden

Policy search reinforcement learning allows robots to acquire skills by themselves. However, the learning procedure is inherently unsafe as the robot has no a-priori way to predict the consequences of the exploratory actions it takes. Therefore, exploration can lead to collisions with the potential to harm the robot and/or the environment. In this work we address the safety aspect by constraining the exploration to happen in safe-to-explore state spaces. These are formed by decomposing target skills (e.g., grasping) into higher ranked sub-tasks (e.g., collision avoidance, joint limit avoidance) and lower ranked movement tasks (e.g., reaching). Sub-tasks are defined as concurrent controllers (policies) in different operational spaces together with associated Jacobians representing their joint-space mapping. Safety is ensured by only learning policies corresponding to lower ranked sub-tasks in the redundant null space of higher ranked ones. As a side benefit, learning in sub-manifolds of the state-space also facilitates sample efficiency. Reaching skills performed in simulation and grasping skills performed on a real robot validate the usefulness of the proposed approach. Copyright © 2018, The Authors. All rights reserved.

关键词： Reinforcement learning

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Relative Confidence Based Information Fusion For Semg-Based Pattern Recognition

Relative Confidence Based Information Fusion For Semg-Based ...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jinrong Li Yinfeng Fang Yong Ning Jing Jie Ping Tan Honghai Liu School of Automation and Electric Engineering Zhejiang University of Science & Technology Hangzhou China Intelligent Systems and Biomedical Robotics Group School of Computing University of Portsmouth Portsmouth UK

ISBN: (纸本)9781538652152

This study aims to establish a decision fusion scheme that synthesize the advantages of different classifiers and avoids uncertain decisions. Thus, relative confidence factors of each classifier was proposed to correct the classification decision made by each classifier, and the final classification result was derived by fusing all corrected decision based on the combination of Dempster-Shafer's rule. The novel fusion scheme is evaluated in the scenario of sEMG-based hand movement identification, in which five classffiers are adopted. The experimental results demonstrated that the novel scheme can obtain higher classification accuracy and stability than the other methods.

关键词： Feature extraction Time-domain analysis Pattern recognition Electromyography Tools Time-frequency analysis

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Automated seam tracking system based on passive monocular vision for automated linear robotic welding process 15

Automated seam tracking system based on passive monocular vi...

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15th IEEE International Conference on Industrial Informatics, INDIN 2017

作者： Weis, Atila A. Mor, Jusoan L. Soares, Luciane B. Steffens, Cristiano R. Drews-Jr, Paulo L. J. De Faria, Matheus F. Evald, Paulo J. D. O. Azzolin, Rodrigo Z. Filho, Nelson D. Botelho, Silvia S. Da C. Intelligent Robotics and Automation Group NAUTEC Science Computer Center - C3 Federal University of Rio Grande Brazil

ISBN: (纸本)9781538608371

Welding is an important process in the industrial scenario, especially in the shipbuilding industry. This process is recognized by the laborious work and the hazardous work environment. The use of robots to automate the welding process can reduce the human interference and improve the productivity. This paper proposes a system for automated seam tracking based on passive monocular vision. The vision provides a data feedback to the automated robotic welding system allowing quality and productivity gains. A trajectory controller is developed to correct the robot's movement over the seam reference. The controller and a visual algorithm to find the seam reference in a real Gas Metal Arc Welding (GMAW) process are presented. The proposed system allows the automated seam tracking, the trajectory control of the welding torch, and a higher automation level in linear robotic welding. The capabilities of the method is evaluated using a commercial linear welding robot showing its viability. © 2017 IEEE.

关键词： Productivity

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An extended Kalman filter state estimation-based robust MRAC for welding robot motor control 43

An extended Kalman filter state estimation-based robust MRAC...

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43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017

作者： De Oliveira Evald, Paulo Jefferson Dias Mor, Jusoan Lang Da Rosa, Romulo Thiago Silva Azzolin, Rodrigo Zelir De Oliveira, Vincius Menezes Da Costa Botelho, Silvia Silva Intelligent Robotics and Automation Group Computer Science Centre Federal University of Rio Grande Rio Grande96201-900 Brazil

ISBN: (纸本)9781538611272

The robotic welding processes have been highly widespread in manufacturing industries due to large-scale production. An area where these processes are widely applied are shipyards, where there are necessary hundreds to thousands of kilograms of weld by hour. However, systems that operate in open-air environments are vulnerable to sundry disturbances, noises in measures, as well as possible unavailability of measurement of some system states, required for the controller. Taking it into account, in this work, a Robust Model Reference Adaptive Control is proposed to regulate the velocity of a nonlinear motor of a linear welding robot. Furthermore, an Extended Kalman Filter is implemented to estimate the system states and attenuate measurement noises. The proposed control system demonstrated a very good performance with fast convergence and small error. © 2017 IEEE.

关键词： Extended Kalman filters

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Velocity regulation of a linear welding robot by unscented and cubature Kalman filter output estimation-based sliding mode control 43

Velocity regulation of a linear welding robot by unscented a...

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43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017

作者： Jefferson Dias De Oliveira Evald, Paulo Silva Da Rosa, Romulo Thiago Mor, Jusoan Lang Azzolin, Rodrigo Zelir De Oliveira, Vincius Menezes Silva Da Costa Botelho, Silvia Intelligent Robotics and Automation Group Computer Science Centre Federal University of Rio Grande Rio Grande96201-900 Brazil

ISBN: (纸本)9781538611272

Welding is an important operation in manufacturing processes and it can represent a highly relevant amount of production costs, depending on material workpieces and required weld quantity. In mechanised and robotised welding processes, robot's travel velocity is an important parameter, which requires a proper regulation to obtain a good quality for weld beam. Then, in this work, a nonlinear model of a robot motor with their identified parameters is presented and a sliding mode control is proposed to regulate robot velocity. Furthermore, an Unscented Kalman Filter and a Cubature Kalman Filter are implemented, separately, for output system estimation. The control system with both estimators presented satisfactory tracking performances, in simulations, converging fast and with very small chattering. © 2017 IEEE.

关键词： Sliding mode control

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Roadmap on soft robotics: multifunctionality, adaptability and growth without borders

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Multifunctional Materials 2022年第3期5卷 032001-032001页

作者： Mazzolai, Barbara Mondini, Alessio Del Dottore, Emanuela Margheri, Laura Carpi, Federico Suzumori, Koichi Cianchetti, Matteo Speck, Thomas Smoukov, Stoyan K. Burgert, Ingo Keplinger, Tobias Siqueira, Gilberto De Freitas Vanneste, Felix Goury, Olivier Duriez, Christian Nanayakkara, Thrishantha Vanderborght, Bram Brancart, Joost Terryn, Seppe Rich, Steven I. Liu, Ruiyuan Fukuda, Kenjiro Someya, Takao Calisti, Marcello Laschi, Cecilia Sun, Wenguang Wang, Gang Wen, Li Baines, Robert Patiballa, Sree Kalyan Kramer-Bottiglio, Rebecca Rus, Daniela Fischer, Peer Simmel, Friedrich C Lendlein, Andreas Bioinspired Soft Robotics Laboratory Istituto Italiano di Tecnologia Italy Department of Industrial Engineering University of Florence Via di S. Marta 3 Florence50139 Italy Department of Mechanical Engineering Tokyo Institute of Technology Ookayama Meguro Tokyo152-8550 Japan The BioRobotics Institute Scuola Superiore Sant’Anna Pisa56025 Italy Department of Excellence in Robotics & AI Scuola Superiore Sant’Anna Pisa56025 Italy Plant Biomechanics Group & Botanic Garden and Cluster of Excellence livMatS @ FIT University of Freiburg Germany Active and Intelligent Materials Laboratory Queen Mary University of London LondonE1 4NS United Kingdom Wood Materials Science Institute for Building Materials ETH Zurich Zurich8093 Switzerland Cellulose and Wood Materials Laboratory Empa Swiss Federal Laboratories for Materials Science and Technology Dübendorf8600 Switzerland University of Lille Inria CNRS Centrale Lille UMR 9189 CRIStAL LilleF-59000 France Dyson School of Design Engineering Imperial College London United Kingdom Vrije Universiteit Brussel and imec Brussels Belgium Thin-Film Device Laboratory RIKEN 2-1 Hirosawa Saitama Wako351-0198 Japan Center for Emergent Matter Science RIKEN 2-1 Hirosawa Saitama Wako351-0198 Japan Electrical and Electronic Engineering and Information Systems The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan The BioRobotics Institute Scuola Superiore Sant’Anna Italy Lincoln Institute for Agri-food Technology University of Lincoln Lincoln United Kingdom Department of Mechanical Engineering National University of Singapore Singapore School of Mechanical Engineering and Automation Beihang University Beijing100191 China Department of Mechanical Engineering and Materials Science Yale University New HavenCT06511 United States CSAIL MIT Schwarzman College of Computing United States Max Planck Institute for Intelligent Systems Heisenbergstr. 3 Stuttgart70569 Germany Institute of Physical Chemistry

Soft robotics aims at creating systems with improved performance of movement and adaptability in unknown, challenging, environments and with higher level of safety during interactions with humans. This Roadmap on Soft robotics covers selected aspects for the design of soft robots significantly linked to the area of multifunctional materials, as these are considered a fundamental component in the design of soft robots for an improvement of their peculiar abilities, such as morphing, adaptivity and growth. The roadmap includes different approaches for components and systems design, bioinspired materials, methodologies for building soft robots, strategies for the implementation and control of their functionalities and behavior, and examples of soft-bodied systems showing abilities across different environments. For each covered topic, the author(s) describe the current status and research directions, current and future challenges, and perspective advances in science and technology to meet the challenges. © 2022 The Author(s). Published by IOP Publishing Ltd.

关键词： Machine design

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