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  • 1. Order onlineBuy this publication >>
    Wallén, Johanna
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Estimation-based iterative learning control2011Doctoral thesis, monograph (Other academic)
    Abstract [en]

    In many  applications industrial robots perform the same motion  repeatedly. One way of compensating the repetitive part of the error  is by using iterative learning control (ILC). The ILC algorithm  makes use of the measured errors and iteratively calculates a  correction signal that is applied to the system.

    The main topic of the thesis is to apply an ILC algorithm to a  dynamic system where the controlled variable is not measured. A  remedy for handling this difficulty is to use additional sensors in  combination with signal processing algorithms to obtain estimates of  the controlled variable. A framework for analysis of ILC algorithms  is proposed for the situation when an ILC algorithm uses an estimate  of the controlled variable. This is a relevant research problem in  for example industrial robot applications, where normally only the  motor angular positions are measured while the control objective is  to follow a desired tool path. Additionally, the dynamic model of  the flexible robot structure suffers from uncertainties. The  behaviour when a system having these difficulties is controlled by  an ILC algorithm using measured variables directly is illustrated  experimentally, on both a serial and a parallel robot, and in  simulations of a flexible two-mass model. It is shown that the  correction of the tool-position error is limited by the accuracy of  the robot model.

    The benefits of estimation-based ILC is illustrated for cases when  fusing measurements of the robot motor angular positions with  measurements from an additional accelerometer mounted on the robot  tool to form a tool-position estimate. Estimation-based ILC is  studied in simulations on a flexible two-mass model and on a  flexible nonlinear two-link robot model, as well as in experiments  on a parallel robot. The results show that it is possible to improve  the tool performance when a tool-position estimate is used in the  ILC algorithm, compared to when the original measurements available  are used directly in the algorithm. Furthermore, the resulting  performance relies on the quality of the estimate, as expected.

    In the last part of the thesis, some implementation aspects of ILC  are discussed. Since the ILC algorithm involves filtering of signals  over finite-time intervals, often using non-causal filters, it is  important that the boundary effects of the filtering operations are  appropriately handled when implementing the algorithm. It is  illustrated by theoretical analysis and in simulations that the  method of implementation can have large influence over stability and  convergence properties of the algorithm.

  • 2.
    Wallén, Johanna
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On Kinematic Modelling and Iterative Learning Control of Industrial Robots2008Licentiate thesis, monograph (Other academic)
    Abstract [en]

    Good models of industrial robots are necessary in a variety of applications, such as mechanical design, performance simulation, control, diagnosis, supervision and offline programming. This motivates the need for good modelling tools. In the first part of this thesis the forward kinematic modelling of serial industrial robots is studied. The first steps towards a toolbox are implemented in the Maple programming language.

    A series of possible applications for the toolbox can be mentioned. One example is to estimate the pose of the robot tool using an extended Kalman filter by means of extra sensors mounted on the robot. The kinematic equations and the relations necessary for the extended Kalman filter can be derived in the modelling tool. Iterative learning control, ILC, using an estimate of the tool position can then improve the robot performance.

    The second part of the thesis is devoted to ILC, which is a control method that is applicable when the robot performs a repetitive movement starting from the same initial conditions every repetition. The algorithm compensates for repetitive errors by adding a correction signal to the reference. Studies where ILC is applied to a real industrial platform is less common in the literature, which motivates the work in this thesis.

    A first-order ILC filter with iteration-independent operators derived using a heuristic design approach is used, which results in a non-causal algorithm. A simulation study is made, where a flexible two-mass model is used as a simplified linear model of a single robot joint and the ILC algorithm applied is based on motor-angle measurements only. It is shown that when a model error is introduced in the relation between the arm and motor reference angle, it is not necessary that the error on the arm side is reduced as much as the error on the motor side, or in fact reduced at all.

    In the experiments the ILC algorithm is applied to a large-size commercial industrial robot, performing a circular motion that is relevant for a laser-cutting application. The same ILC design variables are used for all six motors and the learning is stopped after five iterations, which is motivated in practice by experimental results. Performance on the motor side and the corresponding performance on the arm side, using a laser-measurement system, is studied. Even though the result on the motor side is good, it is no guarantee that the errors on the arm side are decreasing. One has to be very careful when dealing with resonant systems when the controlled variable is not directly measured and included in the algorithm. This indicates that the results on the arm side may be improved when an estimate of, for example, the tool position is used in the ILC algorithm.

  • 3.
    Wallén, Johanna
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On Robot Modelling using Maple2007Report (Other academic)
    Abstract [en]

    This report studies robot modelling by means of the computer algebra tool Maple. First coordinate systems are described, and the more general way with transformation matrices is chosen in the further work. The position kinematics of the robot are then described by homogeneous transformations. The Denavit-Hartenberg representation is used, which is a systematic way to develop the forward kinematics for rigid robots. The velocity kinematics is then described by the Jacobian. The industrial robot IRB1400 from ABB Robotics is used as an example of the theory and to show the use of the procedures developed in the Maple programming language.

  • 4.
    Wallén, Johanna
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Små och stora knep för att få aktivare civilingenjörsstudenter på reglertekniklektionerna2007Report (Other academic)
    Abstract [sv]

    Den här rapporten är en fördjupningsuppgift i pedagogikkursen Lärande, undervisning, kunskap för doktorander. Genom att erbjuda en rad olika inlärningsaktiviteter uppmuntras studenterna att vara mer aktiva med kursinnehållet. Många studenter lär sig som bäst genom att vara aktiva och samarbeta, till exempel i små grupparbeten i och utanför klassrummet. Det kan vara gruppresentationer, små aktiviteter i par under rasten på föreläsningen eller olika typer av samarbeten mellan studenterna. Ett återkommande tips i litteraturen är att införa muntliga presentationer i undervisningen. En ingenjör måste kunna förmedla sina kunskaper, annars lyssnar ingen. Så, varför inte träna detta redan på lektionerna? Det kan till exempel göras så att två studenter skriver ner sina lösningar på varsin tavla. De presenterar sedan lösningarna inför klassen och läraren ingriper om något fel uppstår. Lärarrollen blir en balansakt mellan att låta studenterna diskutera på egen hand och ha egna ideer, och samtidigt säkerställa att diskussionerna är matematiskt produktiva och att kursstoffet täcks.

  • 5.
    Wallén, Johanna
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    The History of the Industrial Robot2008Report (Other academic)
    Abstract [en]

    In this report some phenomena and events in the history of industrial robots have been described. The prerequisites are mainly the early automation in the industry, together with the playful automatons. With the computer and later on the integrated circuit, it was possible to develop the first industrial robots. The first robots were used for simple tasks as pick and place, since they had no external sensing. They replaced humans in monotonous, repetitive, heavy and dangerous tasks. When the robots could manage both a more complex motion, but also had external sensor capacity, more complex applications followed, like welding, grinding, deburring and assembly. The usage of industrial robots can nowadays,roughly speaking, be divided into three different groups; materialhandling, process operations and assembly. In general, industrial robots are used to reduce costs, increase productivity, improve product quality and eliminate harmful tasks. These areas represent the main factors resulting in the spread of robotics technology in a wider and wider range of applications in manufacturing industry. However, introducing robots do not solve all problems. Automation, productivity, employment are complex questions and the connections between robots and labour can be discussed much more.

  • 6.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Henriksson, Robert
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Moberg, Stig
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    ILC Applied to a Flexible Two-Link Robot Model using Sensor-Fusion-Based Estimates2009Report (Other academic)
    Abstract [en]

    Estimates from an extended Kalman filter (EKF) is used in an Iterative Learning Control (ILC) algorithm applied to a realistic two-link robot model with flexible joints. The angles seen from the arm side of the joints (arm angles) are estimated by an EKF in two ways: 1) using  measurements of angles seen from the motor side of the joints (motor angles), which normally  are the only measurements available in commercial industrial robot systems, 2) using both motor- angle and tool-acceleration measurements. The estimates are then used in an ILC algorithm. The results show that the actual arm angles are clearly improved compared to when only motor angles are used in the ILC update, even though model errors are introduced.

  • 7.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Derivation of Kinematic Relations for a Robot using Maple2006In: Proceedings of Reglermöte 2006, 2006Conference paper (Other academic)
    Abstract [en]

    A first step towards making a toolbox in Maple for industrial robot modelling is taken. Position and orientation of the tool can be determined in terms of the Denavit-Hartenberg joint variables and also the Jacobian relating the linear and angular velocities to the joint velocities. Further on it will be possible to, eg, differentiate the Jacobian. Future work includes to evaluate different kinds of sensors and sensor locations and symbolically generate the kinematic models using Maple. It also means to incorporate the models in Matlab- or C-code for including the results, eg, in an Extended Kalman Filter algorithm for state estimation.

  • 8.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Derivation of Kinematic Relations for a Robot using Maple2006Report (Other academic)
    Abstract [en]

    A first step towards making a toolbox in Maple for industrial robot modelling is taken. Position and orientation of the tool can be determined in terms of the Denavit-Hartenberg joint variables and also the Jacobian relating the linear and angular velocities to the joint velocities. Further on it will be possible to, eg, differentiate the Jacobian. Future work includes to evaluate different kinds of sensors and sensor locations and symbolically generate the kinematic models using Maple. It also means to incorporate the models in Matlab- or C-code for including the results, eg, in an Extended Kalman Filter algorithm for state estimation.

  • 9.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Framework for Analysis of Observer-Based ILC2009Report (Other academic)
    Abstract [en]

    A framework for Iterative Learning Control (ILC) is proposed for the situation when the ILC algorithm is based on an estimate of the controlled variable obtained from an observer-based estimation procedure. Under the assumption that the ILC input converges to a bounded signal, a general expression for the asymptotic error of the controlled variable is given. The asymptotic error is then exemplified by an ILC algorithm applied to a flexible two-mass model of a robot joint.

  • 10.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Framework for Analysis of Observer-Based ILC2011In: Asian journal of control, ISSN 1561-8625, E-ISSN 1561-8625, Vol. 13, no 1, p. 3-14Article in journal (Refereed)
    Abstract [en]

    A framework for iterative learning control (ILC) is proposed for the situation when an ILC algorithm uses an estimate of the controlled variable obtained from an observer-based estimation procedure. Assuming that the ILC input converges to a bounded signal, a general expression for the asymptotic error of the controlled variable is given. The asymptotic error is exemplified by an ILC algorithm applied to a flexible two-mass model of a robot joint.

  • 11.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Accelerometer Based Evaluation of Industrial Robot Kinematics Derived in Maple2007In: Proceedings of Mekatronikmöte 2007, 2007Conference paper (Other academic)
    Abstract [en]

    In this paper a step toward making a toolbox for industrial robot modelling based on the computer algebra tool Maple is taken. It can be seen as a modelling platform for efficient derivation of the necessary equations for doing, eg, sensor fusion or state estimation by an Extended Kalman Filter (EKF) algorithm. Forward kinematics is studied and the position and orientation of the robot tool are determined in terms of the Denavit-Hartenberg joint variables. Linear and angular velocities and accelerations are derived using the Jacobian. The toolbox is exemplified using an IRB1400 from ABB Robotics with a so called parallelogram linkage structure. The kinematic relations received are verified using the robot IRB1400 with an accelerometer placed on the robot tool and it is shown that measured acceleration and theoretical acceleration derived from the kinematics agree well. However no flexibilities in the modelling are taken into account, which results in differences between measured and derived acceleration when several motors of the robot cooperate in the motion.

  • 12.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Accelerometer Based Evaluation of Industrial Robot Kinematics Derived in Maple2007Report (Other academic)
    Abstract [en]

    In this paper a step toward making a toolbox for industrial robot modelling based on the computer algebra tool Maple is taken. It can be seen as a modelling platform for efficient derivation of the necessary equations for doing, eg, sensor fusion or state estimation by an Extended Kalman Filter (EKF) algorithm. Forward kinematics is studied and the position and orientation of the robot tool are determined in terms of the Denavit-Hartenberg joint variables. Linear and angular velocities and accelerations are derived using the Jacobian. The toolbox is exemplified using an IRB1400 from ABB Robotics with a so called parallelogram linkage structure. The kinematic relations received are verified using the robot IRB1400 with an accelerometer placed on the robot tool and it is shown that measured acceleration and theoretical acceleration derived from the kinematics agree well. However no flexibilities in the modelling are taken into account, which results in differences between measured and derived acceleration when several motors of the robot cooperate in the motion.

  • 13.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Arm-Side Evaluation of ILC Applied to a Six-Degrees-of-Freedom Industrial Robot2008In: Proceedings of the 17th IFAC World Congress, 2008, , p. 13450-13455p. 13450-13455Conference paper (Refereed)
    Abstract [en]

    Experimental results from a first-order ILC algorithm applied to a large-size sixdegrees-of-freedom commercial industrial robot are presented. The ILC algorithm is based on measurements of the motor angles, but in addition to the conventional evaluation of the ILC algorithm based on the motor-side error, the tool-path error on the arm side is evaluated using a laser-measurement system. Experiments have been carried out in three operating points using movements that represent typical paths in a laser-cutting application and different choices of algorithm design parameters have been studied. The motor-angle error is reduced substantially in all experiments and the tool-path error is reduced in most of the cases. In one operating point, however, the error does not decrease as much and an oscillatory tool behaviour is observed. Changed filter variables can give worse error reduction in all operating points. To achieve even better performance, especially in difficult operating points, it is concluded that an arm-side measurement, from for example an accelerometer, needs to be included in the learning.

  • 14.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Arm-Side Evaluation of ILC Applied to a Six-Degrees-of-Freedom Industrial Robot2007Report (Other academic)
    Abstract [en]

    Experimental results from a first-order ILC algorithm applied to a large-size sixdegrees-of-freedom commercial industrial robot are presented. The ILC algorithm is based on measurements of the motor angles, but in addition to the conventional evaluation of the ILC algorithm based on the motor-side error, the tool-path error on the arm side is evaluated using a laser-measurement system. Experiments have been carried out in three operating points using movements that represent typical paths in a laser-cutting application and different choices of algorithm design parameters have been studied. The motor-angle error is reduced substantially in all experiments and the tool-path error is reduced in most of the cases. In one operating point, however, the error does not decrease as much and an oscillatory tool behaviour is observed. Changed filter variables can give worse error reduction in all operating points. To achieve even better performance, especially in difficult operating points, it is concluded that an arm-side measurement, from for example an accelerometer, needs to be included in the learning.

  • 15.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Comparison of Performance and Robustness for two Classical ILC Algorithms Applied to a Flexible System2008Report (Other academic)
    Abstract [en]

    When an ILC algorithm is applied to an industrial robot, the goal is to move the tool along a desired trajectory, while only the motor position canbe measured. In this paper aspects of robustness and performance are discussed when an ILC algorithm is applied to a flexible two-mass system. It is shown that the stabilising controller of the two-mass system also directly affects the robustness properties of the ILC algorithm. A classical noncausa lP-ILC algorithm and a model-based ILC design using optimisation are applied to the system, based on the error for the first mass. Performance and robustness of the algorithms are compared when model errors are introduced in the system, showing that the optimisation-based approach can handle larger model uncertainties. It is illustrated that the performance of the overall system, when considering position of the second mass, is the practical limit compared to the limiting factor of the robustness of the ILC algorithms.

  • 16.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Experimental Evaluation of ILC Applied to a Six Degrees-of-Freedom Industrial Robot2007In: Proceedings of the 2007 European Control Conference, 2007Conference paper (Refereed)
    Abstract [en]

    Experimental evaluation of an Iterative Learning Control (ILC) algorithm is presented. The ILC algorithm is applied to all motors of a large size commercial six degrees-of-freedom industrial robot in order to minimise the error measured on the motor angles. The performance of the algorithm is evaluated with respect to the operating point of the robot, the programmed tool velocity, and the design variables of the ILC algorithm. The chosen movements are intended to represent typical paths in a laser cutting application. Even though a fairly simple ILC algorithm is applied, the error reduction is substantial after only five iterations and the algorithm shows good robustness properties.

  • 17.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Experimental Evaluation of ILC Applied to a Six Degrees-of-Freedom Industrial Robot2006Report (Other academic)
    Abstract [en]

    Experimental evaluation of an Iterative Learning Control (ILC) algorithm is presented. The ILC algorithm is applied to all motors of a large size commercial six degrees-of-freedom industrial robot in order to minimise the error measured on the motor angles. The performance of the algorithm is evaluated with respect to the operating point of the robot, the programmed tool velocity, and the design variables of the ILC algorithm. The chosen movements are intended to represent typical paths in a laser cutting application. Even though a fairly simple ILC algorithm is applied, the error reduction is substantial after only five iterations and the algorithm shows good robustness properties.

  • 18.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Performance and Robustness of ILC Applied to Flexible Systems2008In: Proceedings of Reglermöte 2008, 2008, p. 210-216Conference paper (Other academic)
    Abstract [en]

    When an ILC algorithm is applied to an industrial robot, the goal is to move the tool along a desired trajectory, while only the motor position can be measured. In this paper aspects of robustness and performance are discussed when an ILC algorithm is applied to a flexible two-mass system. It is shown that the stabilising controller of the two-mass system also directly affects the robustness properties of the ILC algorithm. A classical non-causal P-ILC algorithm and a model-based ILC design using optimisation are applied to the system, based on the error for the first mass. Performance and robustness of the algorithms are compared when model errors are introduced in the system, showing that the optimisation-based approach can handle larger model uncertainties. It is illustrated that the performance of the overall system, when considering position of the second mass, is the practical limit compared to the limiting factor of the robustness of the ILC algorithms.

  • 19.
    Wallén, Johanna
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Performance of ILC Applied to a Flexible Mechanical System2008Report (Other academic)
    Abstract [en]

    ILC is traditionally applied to systems where the controlled variable is the measured variable. However, in standard industrial robots only the motor angles are measured, while the control objective is to follow a tool path. A modern industrial robot is flexible, and assuming that the mechanical flexibilities are concentrated to the robot joints (elastic gearboxes), a flexible two-mass model can be used to describe a single joint. A P-ILC algorithm is applied to the two-mass model, based on only measured angle of the first mass (motor angle) or estimated angle for the second mass (tool angle). Robustness of the algorithm, and performance when model errors are introduced in the model, are discussed considering the error of the tool angle. First, it can be concluded for a flexible system that the characteristics of the motor-angle reference is essential for the resulting tool angle when the tool angle cannot be measured. Second, using an estimate of the tool angle instead of the explicit motor angle in the ILC update reduces the tool-angle error significantly.

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