Tai ngay!!! Ban co the xoa dong chu nay!!! Robotics in Theory and Practice Edited by Lucia Pachnikova Mikulas Hajduk Robotics in Theory and Practice Selected, peer reviewed papers from the 11th International Conference Industrial, Service and Humanoid Robotics ROBTEP 2012, th th November 14 - 16 2012, Strbske Pleso, High Tatras, Slovakia Edited by Lucia Pachnikova and Mikulas Hajduk Copyright 2013 Trans Tech Publications Ltd, Switzerland All rights reserved No part of the contents of this publication may be reproduced or transmitted in any form or by any means without the written permission of the publisher Trans Tech Publications Ltd Kreuzstrasse 10 CH-8635 Durnten-Zurich Switzerland http://www.ttp.net Volume 282 of Applied Mechanics and Materials ISSN print 1660-9336 ISSN cd 1660-9336 ISSN web 1662-7482 Full text available online at http://www.scientific.net Distributed worldwide by and in the Americas by Trans Tech Publications Ltd Kreuzstrasse 10 CH-8635 Durnten-Zurich Switzerland Trans Tech Publications Inc PO Box 699, May Street Enfield, NH 03748 USA Fax: +41 (44) 922 10 33 e-mail: sales@ttp.net Phone: +1 (603) 632-7377 Fax: +1 (603) 632-5611 e-mail: sales-usa@ttp.net 11th International Conference Robtep 2012 Industrial, service and humanoid robotics 14th – 16th November 2012 Hotel Panorama, Strbske pleso, High Tatras, Slovakia PREFACE Dear Distinguished Authors and Guests It is our pleasure to warmly welcome you to 11th International Conference Robtep 2012, held on 14th – 16th November 2012, Strbske pleso, High Tatras, Slovakia The aim of the Robtep 2012 Conference is to present the latest research and results of scientist such as professors, students, PhD students and engineers related to robotics and manufacturing systems This conference provides opportunities for the different areas delegates to exchange new ideas and application experiences face to face, to establish business or research relations and to find partners for future collaboration in research and projects All papers published in this volume have been peer reviewed through processes administrated by the proceedings editors Reviews were conducted by experts referees to the professional and scientific standards The conference program is rich, we would like to thank to all who presented their papers, and our special thanks go to Dr Cecile Huet from European Commission for her interesting presentation of European Framework Programme and Horizon 2020 Programme as well as to Mr Elmo Shreder from euRobotics for his interesting presentation of European Robotics Platforms and possibilities to join them We’d like to extend our thanks to members of scientific committee for their effort to the conference; especially, we’d like to thank to members of organizing committee for their hard working; finally, we would like to express our appreciations to the participants of this conference The Robtep conference is organized within the project “Research of modules for intelligent robotic systems”, ITMS No 2622022141, OPVaV 2009/2.2/05 SORO With our warmest regards prof Ing Mikulas Hajduk, PhD Conference Organizing Chair Committees: Guarantee of conference and scientific committee Dr.h.c prof Ing Anton IŽMÁR, CSc Dr.h.c mult prof Ing František TREBU A, CSc prof Ing Mikuláš HAJDUK, PhD prof Ing Juraj SMR EK, PhD prof Ing Vladimír OP, DrSc Ing Jaromír JEZNÝ, PhD Ing Ladislav VARGOV ÍK, PhD Ing Peter JEN ÍK P Blecha C Bungau P Deme K Dobrovodský F urovský M Ganea C Gưloglu M Haun Š Havlík N Jesse L Jurišica J.H Kim S Klimenko R Knoflí ek Z Kolíbal M Ková P Kopacek J Lunarski T Mikojaczyk A Meyveci L Mostýn T Nieszporek F Novotný F Novák A Olaru G Patko Z Pilat T Popov M Radev A Rovetta J Smolik J Ska upa P Sin ák S Sofianopoulov J Suchy A wi V Szabajkovicz F Šolc W Taranenko R Tarca D Tesar M Tolnay K Velíšek T Vesselenyi I Veža Trends in industrial robotics development Mikuláš Hajduk1, a , Peter Jenčík2, b , Jaromír Jezný3, c, Ladislav Vargovčík4, c Technical University of Kosice, Faculty of Mechanical Engineering, Department of Production Systems and Robotics, B Nemcovej 32, 042 00 Kosic, Slovak Republic Manex, s.r.o., Alvinczyho 12, 040 01 Kosice, Slovak Republic ZŤS VVÚ, 040 01 Kosice, Slovak Republic a mikulas.hajduk@tuke.sk, bpeter.jencik@manex.sk,cjaromir.jezny@ztsvvu.eu, c ladislav.vargovcik@ztsvvu.eu Keywords: industrial robotics, multirobotic cells, duo robots, industrial mobile robots, co-worker robots Abstract The article describes the development and defines the change of approach in the development of today's industrial robotics, provides an overview of the latest trends in the field of industrial robotics Until now, the industrial robots have been deployed to less demanding work environments to perform "only" handling operations and to synchronize the operations of individual facilities Now they are undergoing a major innovation process, the bulk of which is focused on increasing their intelligence and multi-functionality Introduction Industrial robots are expanding from automotive to food, pharmaceutical and chemical industries, also in logistics and recycling processes They can be installed as a replacement for "disposable" tool, as well as at workplaces where greater flexibility is required, so that these robots fill in the gaps of hand actions in automated lines and using the 3D visual systems they provide great opportunities for application in palletization of irregularly incoming objects such as from the line or the press, and in sorting activities Wide application possibilities of robots require managing their design based on a modular principle allowing the construction of a variety of kinematic configurations of robots, as well as of effectors and flexible and intelligent control The times when a robot was only suitable for repetitive handling operations are gone Today's range of robots includes nanorobots which are capable of handling molecules, large robots with capacity of more than 000 kg and robots for virtually every manufacturing and non-manufacturing sector, but also in radioactive environments, sea and space, and there are less and less areas without the use of robots So far we have been looking for new areas to use robots but we have reached the point of asking a question: “Is there an area where the use of robot has not been possible yet?” Robotics development in the world At the forefront of the global development of robotics are Japan, The USA, Europe and South Korea (Fig 1) The USA dominates in service robotics for military use deploying mobile robots type off-road They are unique in the field of space robots and in the development of interplanetary robots Interestingly, the USA does not dominate in industrial robotics, even though robots were first manufactured in the U.S (General Motors, Cincinnati Milacron, Westinghouse and General Electric) Well-known manufacturers of industrial robots in the U.S today are only Adept and San Jose-based Company In Japan and South Korea research activities and production of service robotics are widely developed, humanoid robots includes These robots are primarily focused for household jobs, entertainment or rescue work It turns out to be one of the most traded goods in the next 10 years Japan and South Korea see great potential in the development of robots for elderly care Japan has traditionally been strong in industrial robotics Industrial robots and service robotics dominate in Europe These are focused on mobile robotics, transport and logistics, and especially in the external environment (in urban environment) The second area is represented by robots to work with humans Europe is the leader in manufacturing and deploying industrial robots (with 33% representation) There are about 15 major companies producing industrial robots in Europe (KUKA, ABB, Reis, SCHUNK, STAUBLI, PROMOT, COMAU, CLOOS, FATRONIC) Fig The distribution of the global development of robotics There are a few dominant national and international programs for robotics research in these areas The USA adopted the document Robotics and Automation Research Priorites for U.S Manufacturing in 2009, which emphasizes that robotics is the key to the transformation of production to achieve high competitiveness In Japan, large companies have their own programs to develop new solutions and applications of robots Also in Europe there are more and more research programs focused on robotics The year 2010 is known as a strong comeback towards industrial robotics This stems from the fact that in 2009 the annual installation of robots fell to 60,000, in 2010 it was already 118,000 in 2011 about the 130000 The upward trend is expected in the next five years and in the 2017, the annual number of installed robots should exceed the value of 200000 This trend is based mainly on dynamic growth of markets and deploying robots, especially in China, South Korea and ASEAN countries Step 3:  cos ( q2) −sin ( q2) ⋅ cos ( 0) sin ( q2) ⋅ sin ( 0) l2⋅ cos ( q2)      cos ( q2 ) ⋅ cos ( ) − cos ( q2 ) ⋅ sin ( ) l2 ⋅ sin ( q2 ) sin ( q2 )   A12( q1 , q2 , q3 , q4) := simplify →     sin ( 0) cos ( 0)    0    (10)  cos ( q2) −sin ( q2)  sin ( q2) cos ( q2)  0  0  l2⋅ cos ( q2)  l2⋅ sin ( q2) 0      In step we made simplifying matrices A12 and we got so transformation matrix containing the matrix of rotation around the Z axis coordinate q2 and transformation component axis in x-direction and y Step 4:  cos ( q3) −sin ( q3) ⋅ cos ( 0) sin ( q3) ⋅ sin ( 0) l3⋅ cos ( q3)  sin ( q3) cos ( q3) ⋅ cos ( 0) −cos ( q3) ⋅ sin ( 0) l3⋅ sin ( q3)  A23( q1 , q2 , q3 , q4) :=  simplify →   sin ( 0) cos ( 0)   0    cos ( q3) −sin ( q3) l3⋅ cos ( q3)   sin ( q3) cos ( q3) l3⋅ sin ( q3)      0   (11) In step 4, we performed simplifying matrices A23 and we got so transformation matrix containing the matrix of rotation around Z axis of the coordinate q3 and translational components in xdirection and y Step 5:  cos ( 0) −sin ( 0) ⋅ cos ( 0) sin ( 0) ⋅ sin ( 0) cos ( 0)   sin ( 0) cos ( 0) ⋅ cos ( 0) −cos ( 0) ⋅ sin ( 0) 0⋅ sin ( 0)  A34( q1 , q2 , q3 , q4) :=  simplify →   0 sin ( 0) cos ( 0) −q4    0 0      −q4   0  0 0 (12) In step 5, we got transformation matrix A34 displacement in direction Z coordinate of q4 Transformation matrices between basic coordinate system and i - thereby coordinate system:  −sin ( q1) cos ( q1) Tb1( q1 , q2 , q3 , q4) := Ab0 ( q1 , q2 , q3 , q4) ⋅ A01( q1 , q2 , q3 , q4) simplify →     cos ( q1)   sin ( q1)  l1  0 1 We multiplied matrix Ab0 with the matrix A01 and we got the resulting matrix Tb1  (13) Tb2( q1 , q2 , q3 , q4) := Tb1( q1 , q2 , q3 , q4) ⋅ A12( q1 , q2 , q3 , q4) simplify →  −cos ( q2) ⋅ sin ( q1) sin ( q1) ⋅ sin ( q2) cos ( q1) −l2⋅ cos ( q2) ⋅ sin ( q1)   cos ( q1) ⋅ cos ( q2) −cos ( q1) ⋅ sin ( q2) sin ( q1) l2⋅ cos ( q1) ⋅ cos ( q2)   sin ( q2) cos ( q2) l1 + l2⋅ sin ( q2)    0   (14) We multipled matrix Tb1 with the matrix A12 and we got the resulting matrix Tb2 Tb3( q1 , q2 , q3 , q4) := Tb2( q1 , q2 , q3 , q4) ⋅ A23( q1 , q2 , q3 , q4) simplify → −cos ( q2 + q3) ⋅ sin ( q1) sin ( q2 + q3) ⋅ sin ( q1) cos ( q1) −sin ( q1) ⋅ ( l3⋅ cos ( q2 + q3) + l2⋅ cos ( q2) )   cos ( q2 + q3) ⋅ cos ( q1) −sin ( q2 + q3) ⋅ cos ( q1) sin ( q1) cos ( q1) ⋅ ( l3⋅ cos ( q2 + q3) + l2⋅ cos ( q2) )    sin ( q2 + q3) cos ( q2 + q3) l1 + l3⋅ sin ( q2 + q3) + l2⋅ sin ( q2)   0   (15) We multipled matrix Tb2 with the matrix A23 and we got the resulting matrix Tb3 Tb4( q1 , q2 , q3 , q4) := Tb3( q1 , q2 , q3 , q4) ⋅ A34( q1 , q2 , q3 , q4) → −cos ( q2 + q3) ⋅ sin ( q1) sin ( q2 + q3) ⋅ sin ( q1) cos ( q1) −sin ( q1) ⋅ ( l3⋅ cos ( q2 + q3) + l2⋅ cos ( q2) ) − q4⋅ cos ( q1)   cos ( q2 + q3) ⋅ cos ( q1) −sin ( q2 + q3) ⋅ cos ( q1) sin ( q1) cos ( q1) ⋅ ( l3⋅ cos ( q2 + q3) + l2⋅ cos ( q2) ) − q4⋅ sin ( q1)    sin ( q2 + q3) cos ( q2 + q3) l1 + l3⋅ sin ( q2 + q3) + l2⋅ sin ( q2)   0   (16) We multipled matrix Tb3 with the matrix A34 and we got the resulting matrix Tb4 Individual coordinates: (17) (18) (19) A graphical representation of the individual arms of the robot: Fig Graphical representation of the workspace arm Fig Graphical representation of the workspace arm Fig Graphical representation of the workspace arm Graphical illustration of the workspace whole robot in axis yz, xy, xz: Fig Workspace in the axis yz Fig Workspace in the axis xy Fig Workspace in the axis xz Conclusion For the direct kinematics is known Base coordinate system positioned at the reference point, what for robots imagine base robot Its mission is to find the position vector of end effector to the basic coordinate system Using the Denavit-Hartenberg method, for solution of direct kinematics of industrial motion robots, is advantageous because it is simple to determine individual matrices Respective transformation matrix to help us portray the robot workspace Software MathCAD was used to simplify relations and to illustrate workspaces For calculation of direct kinematics it is possible to use other calculation methods as for example numerical matrix method or analytical method using Jakobi matrix References [1] J Skařupa, V Mostýn, Teorie průmyslových robotů, vyd Košice : Vienala, 2000 146 s.: Vyd pre SjF TU [2] Robert Grepl, Kinematika a dynamika mechatronických systémů, vyd Brno : CERM, 2007 158 [3] W Wolovich Robotics, Basic Analysis and Design Holt, Rinehart, and Winston, New York, 1985 [4] R P Paul, B E Shimano, and G Mayer., Kinematic control equations for simple manipulators IEEE Trans Systems, Man., and Cybernetics, SMC-ll(6):339–455, 1981 [5] Mark W Spong, Seth Hutchinson, and M Vidyasagar, Robot Modeling and Control Copyright, Malloy, USA: ISBN -10 0-471-64990-2, 2006 [6] Michael Valášek, Kinematika robotických systémů ČVUT v Praze, 2011 [7] Šolc F., Žalud L., Základy robotiky Brno, 2002 [8] Jiří Skařupa, Průmyslové roboty a manipulátory Ediční středisko VŠB – TUO,2007 s 227, ISBN 978-80-248-1522-0 Modelling Maintenance and Renewal in Petri Nets Ing Department of Production Systems and Robotics, alena.peskova@tuke.sk Keywords: maintenance, renewal, optimization techniques, Petri net Abstract In this contribution we are dealing with simulation techniques for efficient use of computing of the schedule maintenance and renewal process Maintenance and renewal process is modelled on the basis of Petri nets Thanks to this approach we can simulate the process of improving the maintenance in order to optimize key criteria of renewal and maintenance The proposed solution is demonstrated on two illustrative examples Introduction In the companies maintenance should belong to an important area that needs attention It is also important to pay attention, to exchange already unrepairable machines Modelling processes helps to simplify complicated systems Maintenance and renewal also belong to demanding processes The output of simulation is more efficient representation of particular process Petri net provides a simulation tool for solving discrete systems, modelling, optimization It is a graphical method for representation of discrete systems [1] Articles dealing with the problem of Petri nets in maintenance are widely known The author in the paper [2] Modeling of System Reliability Using Petri Nets with Aging Tokens presents the dynamic modeling of degrading and repairable complex systems Emphasis is placed on the convenience of modeling for the end user, with special attention being paid to the modeling part of a problem, which is considered to be decoupled from the choice of solution algorithms Futher paper [3] studies the particular case where the maintenance activities are executed by two workshops: a central maintenance workshop and a mobile maintenance workshop The aim is to take into account the resources and maintenance actions for a given operating budget This modular approach for modelling a multi-site structure is proposed to achieve the aim of improving the availability of facilities on production sites while minimising the cost of maintenance 1) defining the problem We have a number of machines required in operation, that are necessary not only to maintain preventively in operational state, but also in case of inconvenient outputs to exchange for new ones For this purpose we have maintenance workers It is necessary to create a schedule of preventive maintenance so that the operation will deliver sufficient performance 2) simulation model of Petri nets Simulation graphic tool solves modelling of a particular system The oriented bipartite graph with the assessment represents places and transitions that are marked in certain places They are being relocated on the basis of predetermined rules according to type of nets [4] Basic marking of graph: place - state of an element or an condition transition event arcs (edges) joint between places and transitions and backwards tokens symbols [4] The following rules are applied: transmission is activated if there are enough tokens on arcs according to terms on arcs actived transition may be or need not be carried out performance of transition removes tokens from the input places and adds tokens to output places place contains all integer non-negative numbers if evaluation of edges are not defined, the same applies to the evaluation marks in the places are defined by their capacity (final, non -final) the initial marking (tokens in places) represents the initial state the transition of marks has its own rules [5] The simulation consists of relocation the tokens from place to place, if the transition is enabled to be carry out Fig.1 Basic Petri net The basic formulation of Petri net : N = (P, T, F, Mo) P T F Mo a set of places a set of transitions set of edges initial state of tokens [5] 3) illustrative example - maintenance This model corresponds to situations where the preventive maintenance is performed in which the machine is operational Fig.2 Petri net - maintenance process, state of the system H = (4,0,2) Picture legend: transitions: events start of maintenance, end of maintenance places: operation, operator, maintenance tokens: operation production machines, operator maintainers We have four production machines in the operation, two maintenance workers (operator) are available Fig.2 In case of start of maintenance - one machine will go out of operation to maintenance and it will take a maintenance worker from operator This maintenance worker will be represented by one token on maintenance place Fig.3 Two situations may occur then : either the previous event is repeated or the end of the inspection occurs Fig.3 Change of state for realization event, state of systems H = (3,1,1) Graph G = (V,H) Possible states of change: The set of edges: (3,1,1), (3,1,1) (2,2,0), (2,2,0) (3,1,1), (3,1,1) (4,0,2) } The set of vertices: V={ (3,1,1), (2,2,0), (3,1,1), (4,0,2) } Interpretation of the vertices PN i.e State of system M = (M1,M2,M3) where: M1 = operation with given number of machines M2 = maintenance, action of maintenance workers on machines, it is assumed that during maintenance maintenance worker is necessary for machine M3 = operator, the number of waiting maintenance workers to request of maintenance t1 = transition allowing start of maintenance t2 = transition allowing end of maintenance 4) illustrative example - maintenance and renewal This model is extended by machines that require renewal, ie unrepairable machines are replaced by new ones Fig.4 Petri net - maintenance and renewal process We have five machines available for operation There is machine in stock, that it is necessary to be replaced and it is not possible to be repaired anymore We have three maintenance workers in service In case transition (t1) is actived - start of maintenance - machine from operations (M1) goes to maintenance areas (M2) and one maintenance worker leaves the place (M3) Fig At the same time renewal in the site (M4) can occur so that from stock (M6) machine is taken and is moved through activated transition (t3) to place (M4) with maintenance worker, which is available in place (M3 ) There will be a new state of system Fig Interpretation of the vertices PN i.e State of systems M = (M1, M2, M3, M4, M5, M6) where: M1 = operation with a given number of machines M2 = maintenance, action of maintenence workers on machines, it is assumed that during maintenance maintenance worker is necessary for machine M3 = operator, the number of waiting maintenance workers to request of maintenance or renewal of machines M4 = renewal, active of maintenance workers to installing of a new machine instead of the disassembled machine M5 = disposal of machine, it is not able to fulfill its function anymore M6 = requirements for machines requiring renewal t1 = transition allowing start of maintenance t2 = transition allowing end of maintenance t3 = transition allowing start of renewal t4 = transition allowing end of renewal t5 = transition allowing disassembly of machine Fig Change of state for realization event - maintenance and renewal process Conclusion The goal of this paper was to inform about tool for modelling and simulation discrete systems Petri nets We have shown simple model of Petri nets in the maintenance and renewal Based on our experiments possible scenarios for managers of manufacturing companies can be analyzed This model solves synchronization maintenance operations and renewal of production The model simulates states in that can occur in system Furthermore, it is necessary to create stochastic model e.g using colored Petri nets The model needs to be verified on real data Based on the experimental analysis of possible alternatives scenarios for production managers can be analyzed There exists special open source software for preparation of Petri nets - Snoopy and Pipe They are used to solve logistic problems Our proposed model is necessary to be extended for more complex issues of maintenance and renewal, including resolving capacity machine, solution maintenance according to established priorities, etc References [1] Carl Adam Petri and Wolfgang Reisig (2008): Petri net Scholarpedia, 3(4):6477 [2] Vitali Volovoi: Modeling of System Reliability Using Petri Nets with Aging Tokens, Reliability Engineering and System Safety Vol.84, 2004 149 161 [3] Zineb Simeu-Abazi n, Alali Alhouaij Ahmad: Optimisation of distributed maintenance: Modelling an dapplication to the multi-factory production, Reliability Engineering and System Safety 96 (2011) 1564 1575 [4] -2271883-1 [5] Philippe Darondeau, Stephane Demri, Roland Meyer and Christophe Morvan: Petri Net Reachability graphs: Decidability status of first-order properties, Logical Methods in Computer Science Vol 8(4:9)2012, pp 28 www.lmcs-online.org