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Autonomous Visual rover

Sean Day Diante Reid Liem Huynh. Autonomous Visual rover. Project Overview. To create a vehicle that autonomously follows a moving object To design a low cost, mobile robot that can track objects based on image processing Implement all of the parts using the Atmel microcontroller

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Autonomous Visual rover

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  1. Sean Day Diante Reid Liem Huynh Autonomous Visual rover

  2. Project Overview • To create a vehicle that autonomously follows a moving object • To design a low cost, mobile robot that can track objects based on image processing • Implement all of the parts using the Atmel microcontroller • Fire at target object when specified

  3. Requirements • Autonomously track and follow a moving object using color detection • Operate on battery power and not other external source of power • Keep a minimum of 7 inches away from it target at all time. • Operate both indoor and outdoor • Operate for more than one hour on a fully charged battery. • Have a dimension of no more than 14x7x7 inches

  4. Optional Features • Autonomous weapons system • Solar Power • The AVR shall be able to communicate and upload telemetry data to the user via Bluetooth • The AVR shall be able to map its surrounding and navigate to a designated target with GPS.

  5. SensorsManager Guidance, Navigation and Control Environment CMUCam2+ Top Level Diagram Images Centroid and ServoLocation TargetLocation Target Maxbotix LV-EZ2 UltrasonicSignals PWM TargetRange IR Detector On-OffPulses ChassisVelocity Environment Actuators Software Hardware PWM EncoderPatterns

  6. Microcontroller - Arduino • ATMEGA328 • USB Interface • Cross-platform • Easy to program • Open source • Well documented

  7. Printed Circuit Board • PCB123 software • $100 student credit from sunstone • Prototyped on the Arduino board • 2 layer design • Using through hole and surface mount techniques

  8. CMUcam 2+ Vision Sensor Performs image processing duties for AVR Track user defined color blobs at up to 50 Frames Per Second (frame rate depends on resolution and window size settings) Track motion using frame differencing at 26 Frames Per Second Find the centroid of any tracking data Gather mean color and variance data Gather a 28 bin histogram of each color channel Process Horizontally Edge Filtered Images

  9. Image Processing Requirements • Color detection • Motion detection • Flexibility for programming • Ability to distinguish between specified color and other colors in environment • Work efficiently in well lit environment

  10. Image Processing Techniques • Edge Detection • Canny detection • Edges are areas where a jump in intensity from one pixel to the next occurs • Able to reduce the amount of data processed by filtering out useless information

  11. Blob Detection • Middle Mass • Determines if a group of connecting pixels are related to each other by surroundings • Efficient in identifying separate objects in a scene

  12. CMOS vs. CCD Sensor CMOS CCD • Transistor based • Flexible design • Average picture quality • Low power consumption • Low Price • Analog device • Rigid design • Excellent picture quality • Power hungry • Very Expensive

  13. Choosing a Vision System • CMUcam1 • CMUcam2 • CMUcam3 • AVRcam • Logitech QuickCam Orbit AF Webcam + RoboRealm

  14. CMUcam Comparison

  15. CMUcam2+ Software • Open Source Programmable • Hybrid Version of C Language • CMUcamGUI

  16. Why CMUcam2+ • Compact Size • Frame Buffering • Affordable price • Flexible • Multiple Servo Control • User Support

  17. Power Needs

  18. Voltage Regulation • All parts on AVR can run off of 5volts DC •  Stepping Down 7.4 volt battery • LM317 adjustable regulator

  19. Purpose is to keep AVR within 6 inches of target object Be able to fit on front bumper Will not loose the target object Low power consumption Ultrasonic Sensor Requirements

  20. Maxbotics Ultrasonic Sensor • Maxbotics EZ1 • Will easily fit on bumper • Only draws 2mA of current • Easy to interface

  21. Interfacing the Sensor • Pulse Width Modulation • 147 microseconds/inch • Analog Input • (Vcc/512)/inch

  22. Batteries

  23. Chassis • RC car from ToysRus • 4 wheels • 2 front turning wheels • 2 rear wheels for going back and forward • 2 DC motors • Roomy

  24. Servos • DC Motors • RC Servos • Stepper Motors

  25. Sensors Manager • getRange() • Returns range from Ultrasonic Sensor in inches • getVelocity() • Returns velocity from IR detector/reflector in inches/seconds • getCentroid() • Returns centroid location of target in x and y format

  26. Sensors Manager • getPan() • Returns location of panning servo • getTilt() • Returns location of tilting servo • getTime() • Returns microprocessor’s time

  27. GNC • Determine velocity using the encoder wheel and IR detector/reflector

  28. GNC • Tracking the target’s centroid 1 44 88

  29. GNC 128, 0° • CMUcam to Body alignment • Body Frame, CMUcam Frame Servo Positions 46, -90° 210, 90° β Offset = 44 sin( β ) Centroid_B = Centroid_C + Offset

  30. Initialization GNC Navigation Flowchart Locate Centroid Centroid < 34 Centroid > 54 ForwardLeft ForwardRight else no Target’s range <=5 inches? Stop Forward Straight yes

  31. GNC Proportional-Derivative Controller P (Range) Input Output + + Plant - Error - D (Velocity) • Variable speed depends on range from target and how fast the AVR is moving • P and D gains need to be tuned • All control process is done through software • Sum of error terms multiplied by the gains translate to voltage to drive the actuators (Error*Range) + (Error*Velocity) = Voltage

  32. Testing • DC Motor/ H-bridge test • Range Finding Test • CMUcam2+ Pan and Tilt Test

  33. Testing • DC Motor/H-Bridge turning wheels test • IR Detector/Reflector test • IR Detector/Reflector encoding wheel test • Chassis/Locomotion test with turning wheels • Locomotion test with IR detector/reflector

  34. Testing • Locomotion test with ultrasonic sensor stationary target • Locomotion test with ultrasonic sensor moving target • Locomotion test with CMUcam2++ with stationary target • Locomotion test with CMUcam2++ with moving target • Locomotion test with all sensors

  35. Budget

  36. Progress • Part allocation – 90% • Testing – 10% • Design – 95% • Construction/Prototyping – 20% • Total completed -50%

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