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1028:PICARSOSven Paschburg2 System Process Design Problems Design Specifications Hardware Painting System Image Processing Control Software Testing and.

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Presentation on theme: "1028:PICARSOSven Paschburg2 System Process Design Problems Design Specifications Hardware Painting System Image Processing Control Software Testing and."— Presentation transcript:

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2 1028:PICARSOSven Paschburg2 System Process Design Problems Design Specifications Hardware Painting System Image Processing Control Software Testing and Results Project Outcomes Future Work

3 1028:PICARSOSven Paschburg3 Hardware Painting System Image Processing Control Software PICARSO: Cable-driven robot Process standard image formats Reproduce images on vertical surface

4 Processed 1028:PICARSOSven Paschburg4 Image Output End-Effector OriginalPainted

5 1028:PICARSOSven Paschburg5 Cables End-Effector Motor 1 Motor 2 Motor 3 Vertical Wall Cables Image Processing ToolboxRS232 Graphical User Interface Design Environment (GUIDE) (Mathworks 2010) M ATLAB

6 1028:PICARSOSamuel Oosterholt6 Design Problem Design Specifications System Architecture Hardware Painting System Image Processing Control Software Testing and Results Project Outcomes Future Work

7 Goals:  Develop mechanical system Scalable work space size Up to 3×3m Manipulate and stabilise the end-effector Mounting the system: in operation and in testing 1028:PICARSOSamuel Oosterholt7

8 1028:PICARSOSamuel Oosterholt8  Image producing robots  Scalable workspace size Cable driven Hektor (Franke & Lehni 2002)Viktor (Lehni & Rich 2008) Hektor’s actuator configuration Viktor’s actuator configuration PICARSO’s actuator configuration  Two actuators  ‘V’ Configuration  Relies on gravity  Four actuators  ‘X’ Configuration

9 1028:PICARSOSamuel Oosterholt9  Three motors  ‘Y’ configuration  Cables  Upper motors control position  Lower stabilises Reduces cost Full System Render of PICARSO system

10 1028:PICARSOSamuel Oosterholt10 Base Plate Motor Motor Controller Spooling System Cable feeding system Motor Mount

11 1028:PICARSOSamuel Oosterholt11 Motor Mount  Motors parallel to painting surface  Plate mounts to painting surface  Double spool and bearing  Two cables Reduce yaw and pitch Minimise kickback

12  Cables: Spiderwire (Braid fishing line) Ø = 0.30mm T max = 13.6kg Small elasticity  10m of cable 7×7m workspace  Cables attach to turnbuckles  Reorientated by eyebolts and pulleys  Can move pulleys and eyebolts Proximity to canvas Stability 1028:PICARSOSamuel Oosterholt12 180° Motor Mount  Lower mount uses fairleads  180° sweep

13  Hardware selected from Maxon Motors Numerous operation modes Modular components Discounted cost & support 1028:PICARSOSamuel Oosterholt13 250W EC45 Motors and Maxon EPOS2 70/10 Motor Controller

14  Canvas implemented Simulate surface Reduces ripple in wind 1028:PICARSOSamuel Oosterholt14 PICARSO’s easel in the Vibrations Laboratory PICARSO’s easel in the FSAE shed PICARSO’s canvas  Not feasible to wall mount for testing  3.6 × 3.2m easel (working area: 2.8 × 2.8m)  Constrained by testing environment

15 1028:PICARSONeil Yeoh15 Design Problem Design Specifications System Architecture Hardware Painting System Image Processing Control Software Testing and Results Project Outcomes Future Work

16 Goals:  Design an appropriate painting system which: Produces circular patterns (< 3cm) Is fast (> 1Hz) and light (< 3kg) Does not cause instabilities Houses suitable paint capacity Is reliable, durable, and repeatable 1028:PICARSONeil Yeoh16

17 Circular Patterns ( <3cm) Fast ( >1Hz) Light ( <3kg) No Instabilities Paint Capacity Reliable Durable Repeatable Spray Can AirbrushSpray Gun *1 *2*3 17 Three types of painting mechanisms 1028:PICARSONeil Yeoh17 ** Image references at end of slides

18 1028:PICARSONeil Yeoh18 Paint Line Air Line Electrical Signal Compressed Air Line Electrical Air Compressor Air Regulator Automatic Pressure-fed Spray Gun Personal Computer Solenoid Pressurised Paint Canister Paint Regulator *4 *5 *6 *8 *7 *9 ** Image references at end of slides

19  Anest Iwata SGA-101 Automatic Pressure-fed Spray Gun 1028:PICARSONeil Yeoh19 Fluid Adjust Knob Fitting Knob Paint Line Pattern Adjust Knob Air Line Nozzle

20 1028:PICARSONeil Yeoh20  Testing procedure  Ideal Settings identified:  Results: Consistent < 3cm black circles SpecificationSetting Air Pressure2.0 bar Paint Pressure0.5 – 1.0 bar Spray Distance5 – 10 cm Fluid Adjust KnobHalf Turn Spray Duration0.2 – 1.0 s Spray Duration Repeatability

21 1028:PICARSONeil Yeoh21

22 1028:PICARSONeil Yeoh22 Small Sleeve Large Sleeve Bearings Eyebolts Sleeve Shaft Bearing Spacer Spray Gun

23 1028:PICARSONeil Yeoh23

24 1028:PICARSOIan Hooi24 Design Problem Design Specifications System Architecture Hardware Painting System Image Processing Control Software Testing and Results Project Outcomes Future Work

25 Goals:  Develop image processing software to: Transform input image to user specified settings Reproduce input image in binary form Output in Raster (pixel-by-pixel) form Extension Goal: Output in Vector (line) form 1028:PICARSOIan Hooi25

26 1. Input image 2. Resized to appropriate resolution 3. Stretching and refitting 4. Greyscale form Scaled from 0-1 where 0 is black, 1 is white 1028:PICARSOIan Hooi26 Resized Greyscale Original

27 1028:PICARSOIan Hooi27 Fill Image Edge Image  Fill Images: Direct conversion from greyscale  binary  Edge Images: outlines of the image Fill Image Edge Image

28  Converted to binary form Threshold filter 1028:PICARSOIan Hooi28 OriginalBinary: Threshold = 0.25 Binary: Threshold = 0.5Binary: Threshold = 0.75 OriginalBinary: Threshold = 0.25 Binary: Threshold = 0.5Binary: Threshold = 0.75

29  Raster: pixel by pixel approach  Vector: line based approach 1028:PICARSOIan Hooi29 Raster Based OutputVector Based Output Raster Based Output Vector Based Output

30  Image output in binary form 1 represents white 0 represents black  Read and processed by Control Software  Slow to paint 1028:PICARSOIan Hooi30 = 01110 10101 11011 11011 10001 00011

31  Aim: Raster  Vector  Searching Algorithm based on Portrayer (Benedettelli 2008) and Erik’s XY Plotter (2007)  Adjacent pixels  chains  Control software 1028:PICARSOIan Hooi31 =

32 1028:PICARSOJoyce Phan32 Design Problem Design Specifications System Architecture Hardware Painting System Image Processing Control Software Testing and Results Project Outcomes Future Work

33 Goals:  Software for Raster Mode Convert Image Processing output to: Control motors Control spray gun Extension Goals:  Software for Vector Mode  Graphical User Interface (GUI) 1028:PICARSOJoyce Phan33

34 1028:PICARSOJoyce Phan34 Image Processing Output Inverse Kinematics Motor Commands Cable Lengths Positioning Commands Cartesian Co-ordinates Spray Gun Commands xyxy L 1, L 2, L 3 1 0 0 1 on off turns Motor Turn Units Control Software Output Commands

35 1028:PICARSOJoyce Phan35 Vector Mode 01110 10101 11011 11011 10001 00011 Image Processing Output Raster Mode

36 1028:PICARSOJoyce Phan36

37 1028:PICARSOJoyce Phan37 PC Master Solenoid RS232 Digital Output RS232 Motor Controller 1 Slave Motor Controller 2 SlaveMotor Controller 3 Slave Instructions from Master to Slaves via 3 Parallel RS232 links Outputs controlled in Maxon RS232 Communication Protocol

38 1028:PICARSOJoyce Phan38 Motor 3 Motor 2 Motor 1 Position Mode Current Mode Position Mode Driven in steps Current Mode Provides tension Minimises instabilities

39 1028:PICARSOJoyce Phan39 Easy access to user settings during operation

40 1028:PICARSOSven Paschburg40 Design Problem Design Specifications System Architecture Hardware Painting System Image Processing Control Software Testing and Results Project Outcomes Future Work

41 Goals:  Scaled system – µAngelo  Full scale system – PICARSO  Image processing software  Control software  Graphical User Interface (GUI) Extension Goals:  Vector-based painting  Touch screen interface 1028:PICARSOSven Paschburg41

42 1028:PICARSOSven Paschburg42 Kinematics test bed Tri-motor Y-configuration proof of concept Scaled System - µAngelo Oblique angle picture of µAngelo Front view picture of µAngelo Picture of µAngelo’s end-effector

43 1028:PICARSOSven Paschburg43 Raster painting functionality Scalable across a vertical surface Up to 3×3m workspace area Complete a picture in 1 hour Full Scale System - PICARSO Accuracy & Precision Reliability Workspace Resolution Pixel Size Stability Speed Test Metrics

44 100 mm 50 mm 10 mm 25 mm 1028:PICARSOSven Paschburg44 Raster Painting Functionality SpecificationsAchievement Accuracy± 10 mm Precision± 5 mm Workspace Resolution 10 – 100 mm Workspace Resolution (ideal) 10 – 25 mm

45 1028:PICARSOSven Paschburg45 ParameterAchievement Pixel Size (min.)8 mm Pixel Size (ideal)10 mm Raster Painting Functionality 0.2 s0.25 s0.5 s1.0 s 8 mm10 mm16 mm20 mm

46 1028:PICARSOSven Paschburg46 SpecificationsAchievement Stability± 25 mm (z – axis) Raster Painting Functionality z Side view of the end-effector Bottom view of the end-effector yaw pitch roll

47 1028:PICARSOSven Paschburg47 Scalable across a vertical surface SpecificationsAchievement Workspace Area0.5 × 0.5 m to 7.0 × 7.0 m A picture showing the ability of the end-effector to move around the workspace

48 Goals:  Scaled system – µAngelo  Full scale system – PICARSO  Image processing software  Control software  Graphical User Interface (GUI) 1028:PICARSOSven Paschburg48 A 1.8 × 1.8m painted ‘fills’ image of the Mona Lisa Oblique angle picture of µAngelo

49 Extension Goals:  Analog communication  Complete a picture in 1 hour  Vector-based painting  Touch screen interface Future years:  Colour painting  Wireless communication  Commercial product 1028:PICARSOSven Paschburg49

50 1028:PICARSOSven Paschburg50

51  Benedettelli, D. 2008, NXT Portrayer Robot, viewed 11th April 2010  Convict Episcopal de Luxembourg, 2007, Erik’s XY-Plotter, viewed 11th April 2010,.  Franke, U & Lehni, J 2002, Hektor, viewed 29 December 2009,. 1028:PICARSOSven Paschburg51

52 1. Spray can - http://comps.fotosearch.com/comp/UNN/UNN113/spray- can_~u14072509.jpg 2. Airbrush - http://imgs.tootoo.com/e1/00/e10006f419523aa3bb036a77fb5038dd.jpg 3. Spray gun - http://image.made-in-china.com/2f0j00DaTQeBfgIEMJ/HVLP- Spray-Gun-RP8021-2S-H827-S-.jpg 4. Air Compressor - http://toolmonger.com/wp- content/uploads/2006/05/aircompressor.jpg 5. Festo Air Regulator - http://www.festo.com/rep/nl- be_be/assets/LR_2008_1314u.jpg 6. Pressurised Paint Canister - http://www.smitsgroup.co.nz/images/objectimages/PT2-Paint-Tank.jpg 7. Festo Solenoid Valve - http://www.luconda.com/artikeldetails/27/29/xx/bilder/2093457-1-Festo-CPE18- M1H-3GL-1-4.jpg 8. Iwata Spray Gun - http://www.anest- iwata.co.jp/english/products/paint/prd/fog/auto/images/ceramic_ph01.jpg 9. Personal Computer - http://www.ubergizmo.com/photos/2008/12/dell-xps-13.jpg 1028:PICARSOSven Paschburg52

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54 1028:PICARSOSamuel Oosterholt54 Hardware Painting System Image Processing Control Software PICARSO Mechanical & Electrical Software

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56 1028:PICARSOJoyce Phan56

57 1028:PICARSOJoyce Phan57

58 1028:PICARSOJoyce Phan58

59 1028:PICARSOIan Hooi59

60 1028:PICARSOJoyce Phan60 PC Master EPOS2 Slave (Node 1) EPOS2 Slave (Node 2) EPOS2 Slave (Node 3) NI PCI-6221 card (Analogue Inputs) NI SB 68-LP Breakout Board

61 1028:PICARSOJoyce Phan61

62 1028:PICARSOJoyce Phan62

63 1028:PICARSOJoyce Phan63

64 1028:PICARSOSven Paschburg64

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68 1028:PICARSOSven Paschburg68 Raster processing functionality Process an image in less than 60s Vector processing functionality Image Processing Software Processing SettingsOptions Image InputJPEG, PNG, GIF, BMP, TIFF Image Resolution10 – 500 pixels Image Threshold0 – 1 Conversion TypeFills, Edges Palette TypeBinary (Black & White) SizingSquare, Original Aspect Ratio Image Processing Time< 3 s

69 1028:PICARSOSven Paschburg69 Raster functionality Human Machine Interface (HMI) Vector functionality Touch screen interface High Level Control Software SpecificationsOptions Control ModeRaster Painting, Vector Painting, Manual Positioning, Spray Control PlatformMathworks MATLAB 2007 + Operating SystemWindows XP, Vista, 7 Interface TypeGraphical (Touch Screen)

70 1028:PICARSOSven Paschburg70 Position the motors Control the motor velocity and acceleration Read back the current position Actuate the spray gun solenoid Low Level Control Software SpecificationsOptions Control FunctionsPosition Control, Set Max. Velocity & Acceleration, Read Current Position, Activate Digital Output PlatformMathworks MATLAB 2007 + Operating SystemWindows XP, Vista, 7 Positioning Accuracy (theoretical)2.11 × 10 -3 mm

71 1028:PICARSOSven Paschburg71 Complete a picture in 1 hour ParameterSpecification Speed2 – 250 mms -1 Acceleration2 – 150 mms -2 Picture Time (av.)2.5 hrs (edge image) A 1.8 × 1.8m painted ‘fills’ image of the Mona Lisa A 1 × 1m painted ‘edge’ image of the University of Adelaide logo


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