University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007

Team Members Dan Mackin Kyle Huston Farhad Majdeteimouri Muhammad Ahmad

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 Presentation Outline High Level Project Discussion Features Project Overview Components System Block Diagram Self Organizing Map (SOM) Discussion SOM Block Diagram SOM Demo Auto-Calibration Device (“Tapper”) Discussion Tapper Block Diagram MSP430 Development Board Overview Microstepping Motor Controller 3-D Model Project Administration Discussion Division of Labor Updated Timeline Milestones Status Update Updated Costs Risk Analysis and Safeguards Questions?

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 Features Self learning algorithm maps a strand of fiber and displays any touches on the fiber in real time on a computer monitor. Robotic device provides auto-calibration by randomly deflecting the light through the fiber for a finite time. A user is then able to put pressure on the fiber and have its exact location mapped out on the screen.

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 Project Overview Uses Self Organizing Maps (SOM) to model Optical Fiber in Matlab Laser is shone into the optical fiber which produces a speckle pattern that is recorded by a typical webcam which Matlab acquires A robotic tapping device built using a stepper motor, a servo, and a microcontroller will tap on the fiber strand The speckle pattern will change as the robotic tapping device puts pressure on the fiber strand in various locations Hundreds of speckle patterns will be recorded as the tapping device produces random tapping along the fiber The Self-Organizing Map algorithm then learns the topology of the fiber

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 Components SOM Components Personal Computer Matlab Software Optical Hardware Optical Breadboard USB Webcam Multi-Mode Fiber Strand Red Laser Diode Collimating and Condensing Lens Opaque Plexi-Glass Enclosure Tapper Hardware MSP430 Microcontroller and Development Board MD2S-P High Resolution Micostepping Motor Controller STH39C Stepper Motor HS-422 Hi-Tec Deluxe Hobby Servos Derlin Mini-Sprockets and Chains Fiber Glass Enclosure

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 Optical fiber PC running Matlab MSP430 Microcontroller and Development Board Microstepping Motor Controller Provides high resolution Stepper motor movement Servo Powers mechanical tapping arm USB RS-232 Mechanical tapping arm Stepper Motor Drives sprocket and chain Which moves tapping arm Along its track Feedback Pictorial Block Diagram

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 SOM Block Diagram

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 SOM Demo

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 MSP430 Development Board Details about this here

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 MSP430 Board Schematic

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 MD2S-P Microstepping Motor Controller Put some details in here

University of Colorado at Boulder – ECE Capstone – CDR – October 16, D Model View

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 Interfacing Tasks Fiber to PC (SOM Algorithm) Camera captures image and transmits to the PC via USB. Image is acquired as an 640x480 8 bit RGB image. Image is pulled into Matlab using image acquisition toolbox extracts a 200x200 speckle pattern. PC to MSP430 Microcontroller Matlab sends commands to MSP430 using RS232 interface standard. Microcontroller to Tapper Device MSP430 sends digital signals to MD2S-P Microstepping Motor Controller MSP430 sends pulse width modulated signal to hobby servo for tapping arm movement MD2S-P sends required waveform to STH39C stepper motor for tapper device movement Digital switch relays home position of tapping device to MSP430

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 Division of Labor Hardware/Calibration – Kyle, Dan Image Processing – Muhammad, Farhad SOM Algorithm – Farhad, Kyle Display Routines – Dan, Muhammad Breadboard Enclosure Construction – Dan, Kyle Tapper Device Construction – Muhammad, Kyle Tapper Device Programming – Muhammad, Dan

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 Timeline

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 Milestones Milestone One SOM Algorithm Developed Using 50 Neurons Robotic Tapping Device Construction Complete Initial Programming of Tapping Device Complete Milestone Two SOM Algorithm Optimized and Tested Using 200 Neurons Opaque Breadboard Enclosure Complete Robotic Tapping Device Programming Complete System Tested and Integrated

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 Current Status SOM Hardware setup complete Image acquisition and front end image processing complete Initial SOM prototype redesigned to include 50 neurons Tapper Initial control of stepper motor using microcontroller and microstepping motor controller complete Enclosure and tapper schematics and part design 75% complete

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 Updated Costs

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 Risk Analysis and Safeguard Main Risk: It is impossible to save the configuration of the SOM once the algorithm has been calibrated with that specific speckle configuration. Safeguard: We are planning to lock the enclosure such that the laser and all corresponding filters and lenses can not be accessed by anyone thus preventing the need for re-calibration.

University of Colorado at Boulder – ECE Capstone – CDR – October 16, 2007 Questions?