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6.2 CIRCULAR INTERPOLATION In the ELAU GmbH EPAS-4 library there is a function called MoveC. This function needs the following parameters: • Start point, A – Start position for the TCP • End point, B – End position for the TCP • Cirlce point, C – Point between start and end points • Max TCP velocity – The maximum velocity of the TCP when moving along the path The function moves the TCP on a circular path from the starting position A via the arc point C to the target position B. Between the end and start point the curve is divided into several points, see Figure 6.4. Then the distance between every point at the curve is interpolated using cubic spline. Figure 6.4, shows circle spline with the motion between point A to point B divided into several points which are in turn interpolated with cubic spline. The virtual master determines the velocity of the TCP for each cycle. To contain this velocity the x, y and z have different velocities so at the end the TCP trajectory has the desired velocity. 6.3 CUBIC SPLINE Splines represent an alternative approach to data interpolation. In polynomial interpolation, a single formula, given by a polynomial, is used to meet all the data points. The idea of splines is to use several formulas, each a low degree polynomial, to pass trough the data points (14). A cubic spline interpolates between the given data points by degree 3 polynomial. It is used when one want to make a various path with interpolation between many points. In ELAU GmbHs robotic library is this function called MoveSB, and can move the robot in a three-dimensional spline from the start position across a maximum of 100 points to the target position. The cubic spline calculates the smoothes path between each of the data points so at the end a smooth trajectory will be held. ______________________________________________________________________________ Public Report ELAU GmbH, Marktheidenfeld 32
7 CONTROL APPROACH – ELAU GMBH One idea to controls the Delta-3 robot is independent joint control. This strategy regards the manipulator as formed by three independent systems (the three joints) and controls each joint axis as a single-input/single-output system. This is done by in the PacDrive controller C600 calculate the TCP motion with some of the blocks described in chapter 6 depending on which motion that is sought. Then the inverse kinematics is used to transform the TCP position into angle positions for the three arms that are forwarded from the C600 into respectively MC-4 drive every time cycle. The MC-4 also returns an actual value of the three arm angles every time cycle. These returned angle values are only used to calculate how big the tracking error is. The forward kinematics is also used to calculate the initial position of the TCP so the motion from the initial position to the start position of the motion can be calculated. Then during each time cycle the Cartesian tracking error is calculated with help of the forward kinematics. TCP X Y z (x,y,z) Ref Actual C600 <strong>Control</strong>ler Inverse Kinematics Forward Kinematics θ1 θ2 θ3 Ref (θ1 θ2 θ3) Actual θi → θmi θi ← θmi 3 MC-4s 3 Motors + Transmission ______________________________________________________________________________ Public Report ELAU GmbH, Marktheidenfeld 33 Curr θm1 θm2 θm3 Actual Figure 7.1, shows a C600 PacDrive controller connected to three MC-4s . The three MC-4s controls one motor each to actuate the three arms at the Delta-3 robot. θ3 TCP (x,y,z) Arm 1, θ1 Arm 2, θ2 Arm 3, θ3 θ2 Physical geometry Figure 7.1 shows an overview of the Delta-3 robot system where each block is associated to a picture from the real EPAS system. The desired TCP motion for the robot acts as input into the C600 controller which with the kinematics for the Delta-3 robot calculates the desired joint positions to fulfill the desired TCP motion. Before the three reference joint positions are send to respectively MC-4 the joint positions are transformed into the three motor angles, respectively. This is shown in the figure with an empty box in the figure with associated text. The last block Arm1, Arm2 and Arm3 in the figure describes the Delta-3 robots real arms so the last x, y and z components of the TCP position are obtained by the real robots physical geometry. θ1 (x,y,z)
Page 1: ISSN 0280-5316 ISRN LUTFD2/TFRT--58
Page 5: Acknowledgements This Master thesis
Page 8 and 9: 7 Control approach - ELAU GmbH ....
Page 10 and 11: α1 frame rotation angle for arm at
Page 12 and 13: 2 BACKGROUND 2.1 ROBOTICS The word
Page 14 and 15: 2.2.2 SOFTWARE - ELAU GMBH EPAS-4 i
Page 16 and 17: 3 KINEMATICS - SERIAL ROBOT In the
Page 18 and 19: 3.2 INVERSE KINEMATICS When the for
Page 20 and 21: 4 KINEMATICS & KINETICS - DELTA-3 R
Page 22 and 23: 4.3 Forward Kinematics The forward
Page 24 and 25: Figure 4.5, inverse kinematics tran
Page 26 and 27: where & ⎡x& n ⎤ ⎡− lA sin(
Page 28 and 29: 4.7 ACTUATOR DYNAMICS In most exist
Page 30 and 31: The inertia contribution of each up
Page 32 and 33: According to d’Alembert’s princ
Page 34 and 35: 5 TRAJECTORY A trajectory is a path
Page 36 and 37: 6 TRAJECTORY - ELAU GMBH C600 is th
Page 40 and 41: 7.1 MC-4 DRIVE The MC-4 drive is a
Page 42 and 43: Figure 8.2, Simulink model with mot
Page 44 and 45: 9 PARAMETER ESTIMATION To simulate
Page 46 and 47: 10 EXPERIMENTS For the experiments
Page 48 and 49: Figure 11.2, shows the motion of th
Page 50 and 51: Figure 11.6, shows the current I ef
Page 52 and 53: 11.1.2 SIMULINK EXPERIMENT 2 Figure
Page 54 and 55: Figure 11.13, shows the acceleratio
Page 56 and 57: measured actual value from the real
Page 58 and 59: and are shown over the time in seco
Page 60 and 61: Figure 11.23 shows the x, y and z c
Page 62 and 63: Figure 11.27, the blue line shows t
Page 64 and 65: Figure 11.31, the blue line shows t
Page 66 and 67: In Figure 11.36 the blue line repre
Page 68 and 69: 11.2.3 JACOBIAN EXPERIMENT 3 Figure
Page 70 and 71: In Figure 11.44 the blue line repre
Page 72 and 73: 12 CONCLUSIONS In section 11.1 one

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