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Presentation Outline

Presentation Outline. Introduction Company Profile Problem Statement Proposed solution Cost Analysis Deliverables Plan Conclusion. Members Talha Koc Murat Ozkan Ahmet Eris Halit Ates Mehmet Alp Ekici. Company Profile. Company Profile. Task Distribution

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Presentation Outline

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  1. PresentationOutline • Introduction • Company Profile • Problem Statement • Proposedsolution • CostAnalysis • Deliverables • Plan • Conclusion

  2. Members • Talha Koc • Murat Ozkan • Ahmet Eris • Halit Ates • Mehmet Alp Ekici Company Profile

  3. Company Profile TaskDistribution • Programming Talha, Murat • Purchasing Alp, Ahmet • Power analysis&design Halit, Alp, Ahmet • RF analysis&design Talha • Mechanical analysis&design Talha • Control analysis Halit, Murat • Hardware TestingAll • R&D, DocumentationAll

  4. Problem Statement A vehicle that extracts the map of a closed path • Fitsinside a 1m by 1m square • 1 cm accuracy • No hard wiring • Thevehiclewill not start itsoperation on thepath • No overheadcamera • Area of map

  5. Objectives • Inexpensive and high quality • Optimize costand time • High accuracy -Followingline -Mapextraction • Low power consumption

  6. BlockDiagram of Solution

  7. MAP EXTRACTION >>LINE FOLLOWER > SENSORS FOR MAPPING > MAPPING ALGORITHM & DISPLAY > DATA TRANSMISSION

  8. PART LIST • SENSORS • COLOR SENSOR (3) • MOTORS • STEPPER MOTOR (2) • WHEELS • WHEEL (2) • CASTER

  9. LINE FOLLOWER

  10. PART LIST

  11. COLOR SENSORS • Detection of line • Will be 3 - 5 mm above ground • Placed in a row; 2 cm front of centre line • Separated by 1 cm; left to right

  12. MOTOR UNIT STEPPER MOTORS (2) WHEELS (2) CASTER

  13. MOTORS • Stepper Motors • Controlled by digital input • Can be driven slow • Can be used without gearbox • Low error fraction • Having no contact brushes increases life-time • Will be placed 2 cm behind centre line

  14. WHEELS • Rubber wheel for high friction • Small size (r=1cm) for good resolution • Will be connected to motors separately • Like motors; placed 2 cm behind centre line • Will keep chassis 3-5 mm above ground

  15. CASTER • To support robot • Easily moveable • To keep robot balanced • Placed on the middle, 2 cm away from front

  16. MOTION ALGORITHM

  17. GO FORWARD

  18. TURN TURN LEFT TURN RIGHT

  19. FORWARD+TURN GO LEFT GORIGHT

  20. HEAD FORWARD

  21. >LINE FOLLOWER >>SENSORS FOR MAPPING > MAPPING ALGORITHM & DISPLAY > DATA TRANSMISSION MAP EXTRACTION

  22. Sensor data

  23. Why optical mouse sensor? Resolution is independent of encoder Not dependent on wheel size Installation is easy Gives accurate incremental 2-D displacement

  24. Features of optical mouse sensor • Optical navigation technology • High reliability • Low cost • High speed motion detector • High resolution

  25. Reading Distance from OMS Optical Mouse resolution-> 1600 counts per inch -> 630 counts per cm Example: If we read 64 counts in register this means that our car has moved 64/630 cm. 0,101cm

  26. Why digital compass? ADVANTAGES • Easy to implement • Less sensitive to vibrations • High resolution • Low power DISADVANTAGES • Requires calibration • Affected from magnetic material

  27. Validity of data

  28. MAP EXTRACTION >LINE FOLLOWER > SENSORS FOR MAPPİNG > > MAPPING ALGORITHM&DISPLAY > DATA TRANSMISSION

  29. Mapping & Display “Scientistdiscovertheworldthatexists; engineerscreatetheworldthatneverwas.” (Theodore von Karman )

  30. BlockDiagram

  31. Localization – PositionEstimation Q: Howtoestimaterobot’spose withrespectto a global frame? • AbsolutePoseEstimation (GPS,Landmarks,Beacons) • RelativePoseEstimation (DeadReckoning) • AppropriateCombination of 1 & 2

  32. DeadReckoning • Usedextensively in roboticapplications • ClassicalUse: Wheel Encoders • Advantages: Simple,cheap,easy • Drawback: Accumulation of errors • Solution: • Highpresicionopticalmousesensors (ADNS3080) • No kinematicerrors as in wheelencoders • Post filtering ( Kalman/MarkovFilters)

  33. MappingAlgorithm • To model robotsnextposition,weneed: • ΔxandΔypositions • angleα° • Hardware: • OMS-> Δx& Δy • V2Xe-> α°

  34. MappingAlgorithm(cont.)

  35. AreaCalculation

  36. ErrorConsiderations • Is Optical Mouse Sensor goodenoughtosatisfy +-1cm accuracy? F. A. Kanburoglu, E. Kilic, M. Dolen, M., A. B. Koku, A Test SetupforEvaluatingLong-termMeasurementCharacteristics of Optical Mouse Sensors. "Journal of Automation, Mobile Robotics, andIntelligentSystems", 1, (2007),

  37. ErrorConsiderations (cont.) • Pose = Distance + Anglemeasurements • Thesemeasurmentshave ERRORS or NOISE included. Whatto do? • Kalman Filter -> SmartWay of processing data • Makesdistinctionbetweenreliable data & unreliable data • Smoothsouttheeffect of noise

  38. Kalman FilterSimulationfor V2Xe • Assumption of noisy data with %2 error • Tested for hypothetical values in MATLAB FirstOrder Kalman Filter ,R=2 FirstOrder Kalman Filter ,R=100

  39. Display Software • The software on PC side: • Processing of the raw measurement data • Calculation of the next position according to the state equations • Apply filtering, if necessary • Display the new position on screen in simultaneously

  40. Display Software Testing: • MATLAB is used for map building,filtering • MATLAB Serial Port I/O Interface • The CAS Robot NavigationToolbox (GPL) Final Software: • Written in C++ byWh.Electronics • With a GUI showingmapbuildingprocess

  41. Sample GUI (beta)

  42. >LINE FOLLOWER > SENSORS FOR MAPPİNG > MAPPING ALGORITHM&DISPLAY >> DATA TRANSMISSION MAP EXTRACTION

  43. RF Block Diagram • Data: • OMS Measurement • Digital Compass Measurement

  44. WhyATX-34S & ARX-34 ? • HighFrequencyStability • LowCost (ATX->7TL, ARX->10TL) • LowBatteryConsumption(max 10mA) • EasyIntegrationwith PIC • GoodDocumentation

  45. Microcontroller & ATX-34SConnection

  46. ARX-34 & MAX232 Connection

  47. GanttChart

  48. CostAnalysis

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