Control hardware and Condition Monitoring System for Intersector Weld/Cut Robot

Työ sisältää ohjaislaitteiston vertailun ja valinnan rinnakkaisrakenteista robottia varten sekä kunnonvalvontajärjestelmän periaatteiden laadinnan kyseistä robottia varten. Ohjauslaitteisto sisältää teollisuustietokoneen sekä kenttäväylän. Sekä tietokoneesta että väylästä on teoriaosuus ja yksityiskohtaisempi valintaosuus. Teoriaosuudessa selitetään tarkemmin laitteiden toimintaperiaatteista. Valintaosuudessa kerrotaanmiksi jokin tietty laite on valittu käytettäväksi robotin ohjauksessa. Kunnonvalvontateoria ja rinnakkaisrakenteisen robotin kunnonvalvonnan keinot ovat työn toinen osa. Teoriaosa sisältää yleisluonteisen selvityksen vikaantumisesta ja valvonnasta. Erikoisrobotin kunnonvalvonnan keinot esitetään työssä tietyssä järjestyksessä. Ensin esitetään mahdolliset vikatilanteet. Toisessa kohdassa havainnollistetaan vikojen havaitseminen.

Sensor Fusion of Proprioception, Force and Vision in Estimation and Robot

Sensor-based robot control allows manipulation in dynamic environments with uncertainties. Vision is a versatile low-cost sensory modality, but low sample rate, high sensor delay and uncertain measurements limit its usability, especially in strongly dynamic environments. Force is a complementary sensory modality allowing accurate measurements of local object shape when a tooltip is in contact with the object. In multimodal sensor fusion, several sensors measuring different modalities are combined to give a more accurate estimate of the environment. As force and vision are fundamentally different sensory modalities not sharing a common representation, combining the information from these sensors is not straightforward. In this thesis, methods for fusing proprioception, force and vision together are proposed. Making assumptions of object shape and modeling the uncertainties of the sensors, the measurements can be fused together in an extended Kalman filter. The fusion of force and visual measurements makes it possible to estimate the pose of a moving target with an end-effector mounted moving camera at high rate and accuracy. The proposed approach takes the latency of the vision system into account explicitly, to provide high sample rate estimates. The estimates also allow a smooth transition from vision-based motion control to force control. The velocity of the end-effector can be controlled by estimating the distance to the target by vision and determining the velocity profile giving rapid approach and minimal force overshoot. Experiments with a 5-degree-of-freedom parallel hydraulic manipulator and a 6-degree-of-freedom serial manipulator show that integration of several sensor modalities can increase the accuracy of the measurements significantly.

Control of Robot by Means of Human Thought

Brain computer interface (BCI) is a kind of human machine interface, which provides a new interaction method between human and computer or other equipment. The most significant characteristic of BCI system is that its control input is brain electrical activities acquired from the brain instead of traditional input such as hands or eyes. BCI technique has rapidly developed during last two decades and it has mainly worked as an auxiliary technique to help the disable people improve their life qualities. With the appearance of low cost novel electrical devices such as EMOTIV, BCI technique has been applied to the general public through many useful applications including video gaming, virtual reality and virtual keyboard. The purpose of this research is to be familiar with EMOTIV EPOC system and make use of it to build an EEG based BCI system for controlling an industrial manipulator by means of human thought. To build a BCI system, an acquisition program based on EMOTIV EPOC system is designed and a MFC based dialog that works as an operation panel is presented. Furthermore, the inverse kinematics of RV-3SB industrial robot was solved. In the last part of this research, the designed BCI system with human thought input is examined and the results indicate that the system is running smoothly and displays clearly the motion type and the incremental displacement of the motion.

Uuden robottisolun ohjelmointitavan mahdollisuudet pienille ja keskisuurille yrityksille

Robotin ohjelmointi on aikaa vievää ja tarvitsee robotin ohjelmoinnin tuntevan operaattorin toimimaan robotin opettajana. Saadakseen robottisolun kustannustehokkaaksi operaattorilla olisi hyvä olla useampi solu hoidettavanaan samaan aikaan. Tämä ei ole suuri ongelma suurille yrityksille, joissa voi olla kymmeniä robottisoluja. Jos kyseessä on pieni tai keskisuuri yritys, automatisointi-investointi voi jäädä tekemättä ohjelmoinnin vaikeuden aiheuttaman ongelman vuoksi. Diplomityössä keskityttiin tutkimaan robotisointia pienten ja keskisuurten yritysten kannalta. Teoriaosassa on keskitytty robottisolun suunnittelun kannalta tarvittaviin perustietoihin robotin rakenteesta, ohjausjärjestelmästä, ohjelmoinnista sekä turvallisuudesta. Näiden perustietojen lisäksi on huomioitu hitsauksen automatisointia sekä taluttamalla ohjelmoitavan robottisolun tekninen konsepti. Taluttamalla ohjelmoitavan robottisolun konseptin käsittelyosassa on myös perehdytty taluttamalla ohjelmoinnin vaatimiin komponentteihin kuten voima/vääntö-anturi. Robottisolun suunnittelu on tehtävä koneasetuksen vaatimusten mukaan. Turvallisuus osiossa on käsitelty koneasetuksen vaatimuksia koneensuunnittelulle ja käytännön osassa on käsitelty Winnovan taluttamalla ohjelmoitavan robottisolun suunnittelua koneasetuksen ohjeiden mukaan. Käytännön osassa on tutkittu taluttamalla ohjelmoinnin tuomia etuja muihin ohjelmointimenetelmiin nähden sekä suoritettu investointilaskelmat taluttamalla ohjelmoitavasta ja opettamalla ohjelmoitavasta robottisolusta. Koetuloksista nähdään taluttamalla ohjelmoinnin olevan nopeampi ja yksinkertaisempi tapa ohjelmoida robottia kuin opettamalla ohjelmointi. Investointilaskelmien vertailusta nähdään taluttamalla ohjelmoinnin tulevan opettamalla ohjelmointia edullisemmaksi vaihtoehdoksi käyttökustannusten edullisuuden ansiosta.

Coarse Global Visual Localization of a Mobile Robot

Localization, which is the ability of a mobile robot to estimate its position within its environment, is a key capability for autonomous operation of any mobile robot. This thesis presents a system for indoor coarse and global localization of a mobile robot based on visual information. The system is based on image matching and uses SIFT features as natural landmarks. Features extracted from training images arestored in a database for use in localization later. During localization an image of the scene is captured using the on-board camera of the robot, features are extracted from the image and the best match is searched from the database. Feature matching is done using the k-d tree algorithm. Experimental results showed that localization accuracy increases with the number of training features used in the training database, while, on the other hand, increasing number of features tended to have a negative impact on the computational time. For some parts of the environment the error rate was relatively high due to a strong correlation of features taken from those places across the environment.

Learning Robot Motions from Visual Sensing

Learning from demonstration becomes increasingly popular as an efficient way of robot programming. Not only a scientific interest acts as an inspiration in this case but also the possibility of producing the machines that would find application in different areas of life: robots helping with daily routine at home, high performance automata in industries or friendly toys for children. One way to teach a robot to fulfill complex tasks is to start with simple training exercises, combining them to form more difficult behavior. The objective of the Master’s thesis work was to study robot programming with visual input. Dynamic movement primitives (DMPs) were chosen as a tool for motion learning and generation. Assuming a movement to be a spring system influenced by an external force, making this system move, DMPs represent the motion as a set of non-linear differential equations. During the experiments the properties of DMP, such as temporal and spacial invariance, were examined. The effect of the DMP parameters, including spring coefficient, damping factor, temporal scaling, on the trajectory generated were studied.

Flexible multibody dynamics and intelligent control of a hydraulically driven hybrid redundant robot machine

The assembly and maintenance of the International Thermonuclear Experimental Reactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by the robot involve welding, material handling, and machine cutting from inside the VV. The VV is made of stainless steel, which has poor machinability and tends to work harden very rapidly, and all the machining operations need to be carried out from inside of the ITER VV. A general industrial robot cannot be used due to its poor stiffness in the heavy duty machining process, and this will cause many problems, such as poor surface quality, tool damage, low accuracy. Therefore, one of the most suitable options should be a light weight mobile robot which is able to move around inside of the VV and perform different machining tasks by replacing different cutting tools. Reducing the mass of the robot manipulators offers many advantages: reduced material costs, reduced power consumption, the possibility of using smaller actuators, and a higher payload-to-robot weight ratio. Offsetting these advantages, the lighter weight robot is more flexible, which makes it more difficult to control. To achieve good machining surface quality, the tracking of the end effector must be accurate, and an accurate model for a more flexible robot must be constructed. This thesis studies the dynamics and control of a 10 degree-of-freedom (DOF) redundant hybrid robot (4-DOF serial mechanism and 6-DOF 6-UPS hexapod parallel mechanisms) hydraulically driven with flexible rods under the influence of machining forces. Firstly, the flexibility of the bodies is described using the floating frame of reference method (FFRF). A finite element model (FEM) provided the Craig-Bampton (CB) modes needed for the FFRF. A dynamic model of the system of six closed loop mechanisms was assembled using the constrained Lagrange equations and the Lagrange multiplier method. Subsequently, the reaction forces between the parallel and serial parts were used to study the dynamics of the serial robot. A PID control based on position predictions was implemented independently to control the hydraulic cylinders of the robot. Secondly, in machining, to achieve greater end effector trajectory tracking accuracy for surface quality, a robust control of the actuators for the flexible link has to be deduced. This thesis investigates the intelligent control of a hydraulically driven parallel robot part based on the dynamic model and two schemes of intelligent control for a hydraulically driven parallel mechanism based on the dynamic model: (1) a fuzzy-PID self-tuning controller composed of the conventional PID control and with fuzzy logic, and (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self-tuning of the gains of the PID controller, which are implemented independently to control each hydraulic cylinder of the parallel mechanism based on rod length predictions. The serial component of the hybrid robot can be analyzed using the equilibrium of reaction forces at the universal joint connections of the hexa-element. To achieve precise positional control of the end effector for maximum precision machining, the hydraulic cylinder should be controlled to hold the hexa-element. Thirdly, a finite element approach of multibody systems using the Special Euclidean group SE(3) framework is presented for a parallel mechanism with flexible piston rods under the influence of machining forces. The flexibility of the bodies is described using the nonlinear interpolation method with an exponential map. The equations of motion take the form of a differential algebraic equation on a Lie group, which is solved using a Lie group time integration scheme. The method relies on the local description of motions, so that it provides a singularity-free formulation, and no parameterization of the nodal variables needs to be introduced. The flexible slider constraint is formulated using a Lie group and used for modeling a flexible rod sliding inside a cylinder. The dynamic model of the system of six closed loop mechanisms was assembled using Hamilton’s principle and the Lagrange multiplier method. A linearized hydraulic control system based on rod length predictions was implemented independently to control the hydraulic cylinders. Consequently, the results of the simulations demonstrating the behavior of the robot machine are presented for each case study. In conclusion, this thesis studies the dynamic analysis of a special hybrid (serialparallel) robot for the above-mentioned special task involving the ITER and investigates different control algorithms that can significantly improve machining performance. These analyses and results provide valuable insight into the design and control of the parallel robot with flexible rods.

Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

Development of a Control System for a Tele Operated Mobile Robot

Mobile robots are capable of performing spatial displacement motions in different environments. This motions can be calculated based on sensorial data (autonomous robot) or given by an operator (tele operated robot). This thesis is focused on the latter providing the control architecture which bridges the tele operator and the robot’s locomotion system and end effectors. Such a task might prove overwhelming in cases where the robot comprises a wide variety of sensors and actuators hence a relatively new option was selected: Robot Operating System (ROS). The control system of a new robot will be sketched and tested in a simulation model using ROS together with Gazebo in order to determine the viability of such a system. The simulated model will be based on the projected shape and main features of the real machine. A stability analysis will be performed first theoretically and afterwards using the developed model. This thesis concluded that both the physical properties and the control architecture are feasible and stable settling up the ground for further work with the same robot.

Control of a line robot system with Embedded Linux

Many, if not all, aspects of our everyday lives are related to computers and control. Microprocessors and wireless communications are involved in our lives. Embedded systems are an attracting field because they combine three key factors, small size, low power consumption and high computing capabilities. The aim of this thesis is to study how Linux communicates with the hardware, to answer the question if it is possible to use an operating system like Debian for embedded systems and finally, to build a Mechatronic real time application. In the thesis a presentation of Linux and the Xenomai real time patch is given, the bootloader and communication with the hardware is analyzed. BeagleBone the evaluation board is presented along with the application project consisted of a robot cart with a driver circuit, a line sensor reading a black line and two Xbee antennas. It makes use of Xenomai threads, the real time kernel. According to the obtained results, Linux is able to operate as a real time operating system. The issue of future research is the area of embedded Linux is also discussed.

Ohutlevy-yrityksen mekaanisen valmistuksen tehostaminen

Diplomityön tavoitteena on tehostaa ohutlevytuotteita valmistavan yrityksen toimintaa ja parantaa tuotannon ohjattavuutta. Tuotannon tehostamisessa keskitytään minimoimaan asetusajat, pienentämään eräkokoja ja investoimaan valmistusta helpottaviin työkoneisiin tai -laitteisiin. Tuotannon ohjattavuutta kehitetään helpottamalla visuaalista seurantaa, layout-muutoksilla ja FiFo-ohjauksen käyttöönotolla. Kaikilla kehitystoimenpiteillä pyritään lyhentämään tuotannon läpimenoaikaa ja vähentämään keskeneräisen tuotannon määrää. Tavoitteena on luoda pohja Lean-valmistukselle. Kehitystoimenpiteet keskitetään useimmiten pullonkauloiksi muodostuville osastoille. Kapeikkojen avaamisessa hyödynnetään CIM-projektin mukaisesti tehtäviä investointeja. Uudella robottisärmäysyksiköllä mahdollistetaan litistäminen ja särmääminen yhdellä asetuksella. Kokoonpano-osaston sijaintia muutettiin ja osaston layoutista tehtiin linjamainen. Tuotannonohjauksen kehittämiseksi luotiin yksinkertainen kolmen askeleen kehitysmalli.

Dual light barrier method for six degrees of freedom tool center point calibration of an industrial robot

Tool center point calibration is a known problem in industrial robotics. The major focus of academic research is to enhance the accuracy and repeatability of next generation robots. However, operators of currently available robots are working within the limits of the robot´s repeatability and require calibration methods suitable for these basic applications. This study was conducted in association with Stresstech Oy, which provides solutions for manufacturing quality control. Their sensor, based on the Barkhausen noise effect, requires accurate positioning. The accuracy requirement admits a tool center point calibration problem if measurements are executed with an industrial robot. Multiple possibilities are available in the market for automatic tool center point calibration. Manufacturers provide customized calibrators to most robot types and tools. With the handmade sensors and multiple robot types that Stresstech uses, this would require great deal of labor. This thesis introduces a calibration method that is suitable for all robots which have two digital input ports free. It functions with the traditional method of using a light barrier to detect the tool in the robot coordinate system. However, this method utilizes two parallel light barriers to simultaneously measure and detect the center axis of the tool. Rotations about two axes are defined with the center axis. The last rotation about the Z-axis is calculated for tools that have different width of X- and Y-axes. The results indicate that this method is suitable for calibrating the geometric tool center point of a Barkhausen noise sensor. In the repeatability tests, a standard deviation inside robot repeatability was acquired. The Barkhausen noise signal was also evaluated after recalibration and the results indicate correct calibration. However, future studies should be conducted using a more accurate manipulator, since the method employs the robot itself as a measuring device.

Design of traction transmission and suspension systems for an omni-directional mobile robot

This project aims to design and manufacture a mobile robot with two Universal Robot UR10 mainly used indoors. In order to obtain omni-directional maneuverability, the mobile robot is constructed with Mecanum wheels. The Mecanum wheel can move in any direction with a series of rollers attached to itself. These rollers are angled at 45º about the hub’s circumference. This type of wheels can be used in both driving and steering with their any-direction property. This paper is focused on the design of traction system and suspension system, and the velocity control of Mecanum wheels in the close-loop control system. The mechanical design includes selection of bearing housing, couplers which are act as connection between shafts, motor parts, and other needed components. The 3D design software SolidWorks is utilized to assemble all the components in order to get correct tolerance. The driving shaft is designed based on assembled structure via the software as well. The design of suspension system is to compensate the assembly error of Mecanum wheels to guarantee the stability of the robot. The control system of motor drivers is realized through the Robot Operating System (ROS) on Ubuntu Linux. The purpose of inverse kinematics is to obtain the relationship among the movements of all Mecanum wheels. Via programming and interacting with the computer, the robot could move with required speed and direction.