Teacher/Mentor Institute

August 6-7, 2012

Sensors and Programming Logic

David Dominguez

Goals and Objective

Build an understanding of

The Systems Engineering Process

Robot Design

Sensors and instruments

Example Scenario

Programming Logic

The Systems Engineering Process

An iterative** process that translates simply-stated needs into complex systems

Phases of systems engineering process Define mission requirements and constraints Derive system requirements and constraints Design subsystems

Loops** of systems engineering process Requirements loop: Verify derived requirements match

overall mission 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

(Sellers, 2005)

Systems Engineering “V”

Top-down design, bottom-up realization

(DOT diagram)

Robot Design

Be mindful of mass properties Weight & Balance Size, length of arm, etc. Design for stability

Divide and Conquer Break complex tasks into smaller easier to solve sub-

problems. Use CAD to model your game field and your

robot. Maintain documentation even if your ideas failed.

Lesson Learned

Sensors and Instruments

An instrument reads signals converted by a sensor Voltmeter reads the output of a thermocouple 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 Thermocouple converts changes in temperature into

voltage Potentiometer Infrared (IR) sensor Ultrasonic range finder, etc.

General Sensors

IR sensors With programming logic you can differentiate colors to follow

specific lines, determine size, shape and range of surrounding objects

Ultrasonic Range Finder Uses sound to determine range and size of surrounding objects

Light Sensor Photocell that senses light

Optical Shaft Encoders Uses optics to measure both the position and direction of rotation

of a shaft (radial/angular movement) Potentiometers

Variable resistance for voltage gain control Also useful to determine position and direction of radial angles Can be used to calculate displacement velocity and acceleration

Accelerometer Detects acceleration Allows you determine direction, velocity and displacement of a

robot

Robotics Example using a Potentiometer to solve a problem

Scenario 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

Reverse direction and repeating the same tasks in reverse

Repeat Define Requirements and constraints

Cleanroom Scenario

• 1 Motor: Reversible, -100 to 100 proportional output range• 1 Potentiometer: Operating range of 0o-10800o • 1 rail mounted wheel 50cm in circumference, direct drive to motor & potentiometer• At |100| robot velocity = 2m/sec• 1 rev=360o=50cm of displacement; or 0.5m per revolution

15m

3m 3m

Wheel has a circumference of 50cmc = π(dia.)

Datum

Question and Answer

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

Question and Answer

Q: How do we determine robot position in inches and feet?

A: Read the potentiometer value and apply math.

Question and Answer

Q: How do we determine robot position in inches and feet?

A: Read the potentiometer value and apply math.

Example:

Pval= 3894o; c=50cm; 360o per revolution

Displacement, d=number_of_revs * c

number_of_revs = Pval/360o

d=3894o/360o(50cm)=540.83cm or 5.4083m from

datum

Review of Position and its Derivatives

1. Velocity; v = d/t; more accurately v→=Δd/Δt

2. Acceleration; a→=Δv/Δt; units d/s2 or d s-2

3. Jerk; j→=Δa/Δt; units d/s3 or d s-3

4. Jounce aka snap; s→=Δj/Δt; units d/s4 or d s-4

Cleanroom Scenario

• Beginning velocity = 0• Robot accelerates to max velocity at midway (1.5m) point between machines. • Robot decelerates to 0 at 3m and changes wafer cartridge• 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

15m

3m 3m

Datum

Proportional-Integral-Derivative (PID) Theory

(Wikipedia Image)

Setpoint (SP)

Process Variable (PV)

Manipulated Variable (MV)

PID Control

A PID controller reads a sensor computes the desired actuator output by calculating

proportional, integral, and derivative responses summing the three components to compute the output

Proportional depends on the the difference between the set point and the process variable (present error)

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.

(National Instruments, 2011)

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)

PID (proportional) Interrupt Service Routine

Set PointSP

Process VariablePV

Manipulated VariableMVProportional

Gain Constant

PID (proportional) Interrupt Service Routine

(EasyC Sample Project files)

PID (proportional) Interrupt Service Routine Continued

(EasyC Sample Project files)

Control Loop for PID using Potentiometer

(EasyC Sample Project files)

SP PVMV

References

Sellers, J. J. (2005). Understanding Space: An Introduction to Astronautics (3rd ed.). New York, NY: McGraw Hill.

Easy C Documentation and Sample Project Files

National Instruments Tutorial (2011). PID Theory Explained, http://www.ni.com/white-paper/3782/en#toc2

Wescott, Tim, FLIR Systems (2000). PID Control: PID Without a PhD. EE Times-India, http://www.google.com/url?sa=t&rct=j&q=pid%20without%20a%20phd&source=web&cd=1&ved=0CFkQFjAA&url=http%3A%2F%2Figor.chudov.com%2Fmanuals%2FServo-Tuning%2FPID-without-a-PhD.pdf&ei=_VgYUI-lHIXW9QT29IHABw&usg=AFQjCNFWS6tbKLEO6qRCncHB2m6ZBbqtuw&cad=rja