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Teacher/Mentor Institute August 6-7, 2012 Sensors and Programming Logic David Dominguez.

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Presentation on theme: "Teacher/Mentor Institute August 6-7, 2012 Sensors and Programming Logic David Dominguez."— Presentation transcript:

1 Teacher/Mentor Institute August 6-7, 2012 Sensors and Programming Logic David Dominguez

2 Goals and Objective Build an understanding of Build an understanding of The Systems Engineering Process The Systems Engineering Process Robot Design Robot Design Sensors and instruments Sensors and instruments Example Scenario Example Scenario Programming Logic Programming Logic

3 The Systems Engineering Process An iterative ** process that translates simply-stated needs into complex systems An iterative ** process that translates simply-stated needs into complex systems Phases of systems engineering process Phases of systems engineering process Define mission requirements and constraints Define mission requirements and constraints Derive system requirements and constraints Derive system requirements and constraints Design subsystems Design subsystems Loops ** of systems engineering process Loops ** of systems engineering process Requirements loop: Verify derived requirements match overall mission requirements and constraints Requirements loop: Verify derived requirements match overall mission requirements and constraints Design loop: Verify subsystem designs meet system requirements and constraints Design loop: Verify subsystem designs meet system requirements and constraints Validation loop: Verify the overall system design meets mission requirements and constraints Validation loop: Verify the overall system design meets mission requirements and constraints (Sellers, 2005)

4 Systems Engineering V Top-down design, bottom-up realization (DOT diagram)

5 Robot Design Be mindful of mass properties Be mindful of mass properties Weight & Balance Weight & Balance Size, length of arm, etc. Size, length of arm, etc. Design for stability Design for stability Divide and Conquer Divide and Conquer Break complex tasks into smaller easier to solve sub-problems. Break complex tasks into smaller easier to solve sub-problems. Use CAD to model your game field and your robot. Use CAD to model your game field and your robot. Maintain documentation even if your ideas failed. Lesson Learned Maintain documentation even if your ideas failed. Lesson Learned

6 Sensors and Instruments An instrument reads signals converted by a sensor An instrument reads signals converted by a sensor Voltmeter reads the output of a thermocouple Voltmeter reads the output of a thermocouple Thermometer reads the displacement of mercury Thermometer reads the displacement of mercury A sensor is a device that measures a physical quantity and converts it into a signal which can be observed by an instrument A sensor is a device that measures a physical quantity and converts it into a signal which can be observed by an instrument Thermocouple converts changes in temperature into voltage Thermocouple converts changes in temperature into voltage Potentiometer Potentiometer Infrared (IR) sensor Infrared (IR) sensor Ultrasonic range finder, etc. Ultrasonic range finder, etc.

7 General Sensors IR sensors IR sensors With programming logic you can differentiate colors to follow specific lines, determine size, shape and range of surrounding objects With programming logic you can differentiate colors to follow specific lines, determine size, shape and range of surrounding objects Ultrasonic Range Finder Ultrasonic Range Finder Uses sound to determine range and size of surrounding objects Uses sound to determine range and size of surrounding objects Light Sensor Light Sensor Photocell that senses light Photocell that senses light Optical Shaft Encoders Optical Shaft Encoders Uses optics to measure both the position and direction of rotation of a shaft (radial/angular movement) Uses optics to measure both the position and direction of rotation of a shaft (radial/angular movement) Potentiometers Potentiometers Variable resistance for voltage gain control Variable resistance for voltage gain control Also useful to determine position and direction of radial angles Also useful to determine position and direction of radial angles Can be used to calculate displacement velocity and acceleration Can be used to calculate displacement velocity and acceleration Accelerometer Accelerometer Detects acceleration Detects acceleration Allows you determine direction, velocity and displacement of a robot Allows you determine direction, velocity and displacement of a robot

8 Robotics Example using a Potentiometer to solve a problem Scenario Scenario Semiconductor manufacturer needs a robot to load and unload the Applied Materials Centura Avatar Etch machines in a cleanroom Semiconductor manufacturer needs a robot to load and unload the Applied Materials Centura Avatar Etch machines in a cleanroom Deliver the etched wafer to wafer inspection machines located at the end of the robots track Deliver the etched wafer to wafer inspection machines located at the end of the robots track Reverse direction and repeating the same tasks in reverse Reverse direction and repeating the same tasks in reverse Repeat Repeat Define Requirements and constraints Define Requirements and constraints

9 Cleanroom Scenario 1 Motor: Reversible, -100 to 100 proportional output range 1 Motor: Reversible, -100 to 100 proportional output range 1 Potentiometer: Operating range of 0 o o 1 Potentiometer: Operating range of 0 o o 1 rail mounted wheel 50cm in circumference, direct drive to motor & potentiometer 1 rail mounted wheel 50cm in circumference, direct drive to motor & potentiometer At |100| robot velocity = 2m/sec At |100| robot velocity = 2m/sec 1 rev=360 o =50cm of displacement; or 0.5m per revolution 1 rev=360 o =50cm of displacement; or 0.5m per revolution 15m 3m 3m Wheel has a circumference of 50cm c = π(dia.) Datum

10 Question and Answer Q: How do we determine robot position in cm and/or m? Q: How do we determine robot position in cm and/or m?

11 Question and Answer Q: How do we determine robot position in inches and feet? Q: How do we determine robot position in inches and feet? A: Read the potentiometer value and apply math. A: Read the potentiometer value and apply math.

12 Question and Answer Q: How do we determine robot position in inches and feet? Q: How do we determine robot position in inches and feet? A: Read the potentiometer value and apply math. A: Read the potentiometer value and apply math. Example: Example: P val = 3894 o ; c=50cm; 360 o per revolution P val = 3894 o ; c=50cm; 360 o per revolution Displacement, d=number_of_revs * c Displacement, d=number_of_revs * c number_of_revs = Pval/360 o number_of_revs = Pval/360 o d=3894 o /360 o (50cm)=540.83cm or m from datum d=3894 o /360 o (50cm)=540.83cm or m from datum

13 Review of Position and its Derivatives 1. Velocity; v = d/t; more accurately v =Δd/Δt 2. Acceleration; a =Δv/Δt; units d/s 2 or d s Jerk; j =Δa/Δt; units d/s 3 or d s Jounce aka snap; s =Δj/Δt; units d/s 4 or d s -4

14 Cleanroom Scenario Beginning velocity = 0 Beginning velocity = 0 Robot accelerates to max velocity at midway (1.5m) point between machines. Robot accelerates to max velocity at midway (1.5m) point between machines. Robot decelerates to 0 at 3m and changes wafer cartridge Robot decelerates to 0 at 3m and changes wafer cartridge Repeat until the end where robot places etched wafers in the inspection bin Repeat until the end where robot places etched wafers in the inspection bin Reverses track and repeat the tasks depositing etched wafers at bin on opposite side Reverses track and repeat the tasks depositing etched wafers at bin on opposite side 15m 3m 3mDatum

15 Proportional-Integral-Derivative (PID) Theory (Wikipedia Image) Setpoint (SP) Process Variable (PV) Manipulated Variable (MV)

16 PID Control A PID controller A PID controller reads a sensor reads a sensor computes the desired actuator output by calculating proportional, integral, and derivative responses computes the desired actuator output by calculating proportional, integral, and derivative responses summing the three components to compute the output summing the three components to compute the output Proportional depends on the the difference between the set point and the process variable (present error) Proportional depends on the the difference between the set point and the process variable (present error) Integral component sums the error term over time Integral component sums the error term over time Derivative response is proportional to the rate of change of the process variable. It is a prediction of future errors, based on current rate of change. Derivative response is proportional to the rate of change of the process variable. It is a prediction of future errors, based on current rate of change. (National Instruments, 2011)

17 Sample Motor Response Shows the step input and the motor response using a time constant value of t0 = 0.2s. The response of the motor starts out slowly due to the time constant, but once that is out of the way the motor position ramps at a constant velocity. (Wescott, 2000)

18 PID (proportional) Interrupt Service Routine Set Point SP Process Variable PV Manipulated Variable MV ProportionalGainConstant

19 PID (proportional) Interrupt Service Routine (EasyC Sample Project files)

20 PID (proportional) Interrupt Service Routine Continued (EasyC Sample Project files)

21 Control Loop for PID using Potentiometer (EasyC Sample Project files) SPPV MV

22 References Sellers, J. J. (2005). Understanding Space: An Introduction to Astronautics (3rd ed.). New York, NY: McGraw Hill. Sellers, J. J. (2005). Understanding Space: An Introduction to Astronautics (3rd ed.). New York, NY: McGraw Hill. Easy C Documentation and Sample Project Files Easy C Documentation and Sample Project Files National Instruments Tutorial (2011). PID Theory Explained, National Instruments Tutorial (2011). PID Theory Explained, Wescott, Tim, FLIR Systems (2000). PID Control: PID Without a PhD. EE Times- India, e=web&cd=1&ved=0CFkQFjAA&url=http%3A%2F%2Figor.chudov.com%2Fma nuals%2FServo-Tuning%2FPID-without-a-PhD.pdf&ei=_VgYUI- lHIXW9QT29IHABw&usg=AFQjCNFWS6tbKLEO6qRCncHB2m6ZBbqtuw&cad=rja Wescott, Tim, FLIR Systems (2000). PID Control: PID Without a PhD. EE Times- India, e=web&cd=1&ved=0CFkQFjAA&url=http%3A%2F%2Figor.chudov.com%2Fma nuals%2FServo-Tuning%2FPID-without-a-PhD.pdf&ei=_VgYUI- lHIXW9QT29IHABw&usg=AFQjCNFWS6tbKLEO6qRCncHB2m6ZBbqtuw&cad=rja e=web&cd=1&ved=0CFkQFjAA&url=http%3A%2F%2Figor.chudov.com%2Fma nuals%2FServo-Tuning%2FPID-without-a-PhD.pdf&ei=_VgYUI- lHIXW9QT29IHABw&usg=AFQjCNFWS6tbKLEO6qRCncHB2m6ZBbqtuw&cad=rja e=web&cd=1&ved=0CFkQFjAA&url=http%3A%2F%2Figor.chudov.com%2Fma nuals%2FServo-Tuning%2FPID-without-a-PhD.pdf&ei=_VgYUI- lHIXW9QT29IHABw&usg=AFQjCNFWS6tbKLEO6qRCncHB2m6ZBbqtuw&cad=rja


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