0 Test Slide Text works. Text works. Graphics work. Graphics work.

Self-Mapping Mobile Robot Senior Capstone Project Department of Electrical and Computer Engineering Bradley University Advisor: Dr. A. Malinowski Presented by Stephanie Luft 27 April 2006

2 Presentation Outline Project Overview Project Overview System Block Diagram System Block Diagram Functional Description Functional Description Design Process Design Process Conclusion Conclusion Questions Questions

3 Presentation Outline Project Overview Project Overview System Block Diagram System Block Diagram Functional Description Functional Description Design Process Design Process Conclusion Conclusion Questions Questions

4 Project Overview Objective: To develop a robot that will Objective: To develop a robot that will Map an area of its environment Map an area of its environment Locate itself within the map Locate itself within the map Orient itself within the environment Orient itself within the environment

5 Applications Military Robot (PackBot) Military Robot (PackBot) Household Robot (Roomba) Household Robot (Roomba) Moon or Mars Rover Moon or Mars Rover

6 Review of Previous Work GuideBot Capstone Project 2005 by John Hathway and Dan Leach GuideBot Capstone Project 2005 by John Hathway and Dan Leach Laser Meter: From Drexel University Laser Meter: From Drexel University Thesis: “Concurrent Map Building and Self- Localization for Mobile Robot Navigation” Thesis: “Concurrent Map Building and Self- Localization for Mobile Robot Navigation”

7 Presentation Outline Project Overview Project Overview System Block Diagram System Block Diagram Functional Description Functional Description Design Process Design Process Conclusion Conclusion Questions Questions

8 System Block Diagram

9 MapBot

10 MapBot Robot Platform User Commands

11 MapBot Laser Distance Meter

12 MapBot Map, Robot Location Robot Movement Audio Warning

13 Presentation Outline Project Overview Project Overview System Block Diagram System Block Diagram Functional Description Functional Description Design Process Design Process Conclusion Conclusion Questions Questions

14 Software Functionality MATLAB MATLAB Server/C++ Server/C++ Functional Modes: Functional Modes: Mapping Mapping Maneuvering Maneuvering

15 Software: Mapping Mode Plot environment and locate robot Plot environment and locate robot Distance sensing Distance sensing Immediate response Immediate response Data transmission Data transmission Plotting – obstacles and robot location Plotting – obstacles and robot location Self-locating Self-locating Previous map identification Previous map identification Navigation and maneuvering Navigation and maneuvering

16 Software: Mapping Mode Plot environment and locate robot Plot environment and locate robot Distance sensing Distance sensing Immediate response Immediate response Data transmission Data transmission Plotting – obstacles and robot location Plotting – obstacles and robot location Self-locating Self-locating Previous map identification Previous map identification Navigation and maneuvering Navigation and maneuvering

17 Software: Maneuvering Mode Allow user to control robot Allow user to control robot User interface User interface Data transmission Data transmission Immediate response Immediate response Navigation and maneuvering Navigation and maneuvering Distance sensing Distance sensing Self-locating Self-locating Plotting – robot location only Plotting – robot location only

18 Software: Maneuvering Mode Allow user to control robot Allow user to control robot User interface User interface Data transmission Data transmission Immediate response Immediate response Navigation and maneuvering Navigation and maneuvering Distance sensing Distance sensing Self-locating Self-locating Plotting – robot location only Plotting – robot location only

19 Presentation Outline Project Overview Project Overview System Description System Description Design Process Design Process Conclusion Conclusion Questions Questions

20 Main Program Flowchart Start Take Mapping Readings with Laser Distance Meter Plot Obstacle and Robot Location Probabilities on Map Compare Current Map to Previous Maps Maneuver as Needed

21 Design Theory: Distance Meter Target LASER Focal Plane Camera pfc D h 

22 Design Theory: Distance Meter Guiding Equation: D = h Guiding Equation: D = h tan(pfc*m+b) tan(pfc*m+b) D = distance in meters D = distance in meters h = distance (meters) between laser and center of lens h = distance (meters) between laser and center of lens pfc = pixels from center of image pfc = pixels from center of image m = calibration coefficient m = calibration coefficient b = calibration offset b = calibration offset

23 Design Theory: Distance Meter Results of calibration data Results of calibration data h = m h = m m = m = b = b = Final Equation: D = Final Equation: D = pfc* – pfc* –

24 Design Theory: Mapping Probabilistic Algorithm Probabilistic Algorithm Pixel value range: 0 to 1 (white to black) Pixel value range: 0 to 1 (white to black) Initial pixel value:.25 (light gray) Initial pixel value:.25 (light gray) Obstacle: +.25 Obstacle: +.25 Empty space: -.25 Empty space: X W A L R L

25 Design Theory: Mapping Probabilistic Algorithm Probabilistic Algorithm Pixel value range: 0 to 1 (white to black) Pixel value range: 0 to 1 (white to black) Initial pixel value:.25 (light gray) Initial pixel value:.25 (light gray) Obstacle: +.25 Obstacle: +.25 Empty space: -.25 Empty space: X W A L R L

26 Design Theory: Mapping Probabilistic Algorithm Probabilistic Algorithm Pixel value range: 0 to 1 (white to black) Pixel value range: 0 to 1 (white to black) Initial pixel value:.25 (light gray) Initial pixel value:.25 (light gray) Obstacle: +.25 Obstacle: +.25 Empty space: -.25 Empty space: X W A L R L

27 Design Theory: Mapping Probabilistic Algorithm Probabilistic Algorithm Pixel value range: 0 to 1 (white to black) Pixel value range: 0 to 1 (white to black) Initial pixel value:.25 (light gray) Initial pixel value:.25 (light gray) Obstacle: +.25 Obstacle: +.25 Empty space: -.25 Empty space: W A L R L

28 Design Theory: Mapping Probabilistic Algorithm Probabilistic Algorithm Pixel value range: 0 to 1 (white to black) Pixel value range: 0 to 1 (white to black) Initial pixel value:.25 (light gray) Initial pixel value:.25 (light gray) Obstacle: +.25 Obstacle: +.25 Empty space: -.25 Empty space: W A L R L

29 Shape of room Design Simulation: Mapping Simulating the mapping algorithm using imaginary data Simulating the mapping algorithm using imaginary data This demonstrates that the mapping algorithm works for a simple case This demonstrates that the mapping algorithm works for a simple case

30 Design Testing: Mapping Actual Map taken at the Student Expo Actual Map taken at the Student Expo Mirror Effect Mirror Effect Outliers Outliers Actual Shape of Environment

31 Design Testing: Mapping Actual Map taken at the Student Expo Actual Map taken at the Student Expo Mirror Effect Mirror Effect Outliers Outliers Actual Shape of Environment

32 Presentation Outline Project Overview Project Overview System Description System Description Design Process Design Process Conclusion Conclusion Questions Questions

33 Results: Laser Distance Meter Laser Distance Meter Testing Laser Distance Meter Testing Good mid-distance fit Good mid-distance fit Average 2% error Average 2% error Higher errors at ends Higher errors at ends 12% at edges of range 12% at edges of range Absolute Maximum Range: 0.5 to 175 meters Absolute Maximum Range: 0.5 to 175 meters

34 Results: Laser Distance Meter = Measured Data = Calculated Data

35 Results Mapping Mapping Multiple mappings from same location Multiple mappings from same location PTU Control PTU Control Complete (Thank you, Dr. Malinowski!) Complete (Thank you, Dr. Malinowski!) Robot Movement Robot Movement

36 Future Work Web Control for Remote User Web Control for Remote User Navigation Navigation Enhanced Capabilities Enhanced Capabilities Bright Sunlight Bright Sunlight Stairs Stairs Greater Distance Meter Accuracy Greater Distance Meter Accuracy Power Conservation Power Conservation

37 Results: Complete Mapping Sequence “Second Round” Map Taken in the EE Student Lounge “Second Round” Map Taken in the EE Student Lounge Actual Shape of Environment

Self-Mapping Mobile Robot Questions? Department of Electrical and Computer Engineering Bradley University Advisor: Dr. A. Malinowski Presented by Stephanie Luft 27 April 2006

39 Self-Mapping Mobile Robot Website:

40 Review of Previous Work GuideBot Capstone Project 2005 GuideBot Capstone Project 2005 John Hathway and Daniel Leach John Hathway and Daniel Leach Laser Meter: From Drexel University Laser Meter: From Drexel University Mapping: From Dartmouth University, 1999 Mapping: From Dartmouth University, paper.html paper.html Thesis: “Concurrent Map Building and Self-Localization for Mobile Robot Navigation” Thesis: “Concurrent Map Building and Self-Localization for Mobile Robot Navigation” Thomas Duckett, Manchester, United Kingdom Thomas Duckett, Manchester, United Kingdom

41 Software Flowchart: Basic Mapping, Part 1 Start: Distance Meter Capture Image from Webcam Calculate Distance to Obstacle Place Distance and  into Matrices for Mapping Repeat for 320 °

42 Software Flowchart: Basic Mapping, Part 2 Start: Mapping Initialize Variables and Create or Retrieve Initial Map Calculate Coordinates of Obstacles “Grow” the map to accommodate new obstacles, retaining previous map details Plot obstacles on the map Compare to Previous Maps and Adjust as Necessary