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Motion Tracking & Position Acquisition. Final Presentation. Solomon Gates | William K. Grefe | Jay Michael Heidbreder | Jeremy Kolpak. Overview of Project Objective. Primary Goal Achieve accurate and precise motion of laser pointer directed at a locator beacon Secondary Goal - PowerPoint PPT Presentation
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Motion Tracking &Position
AcquisitionFinal Presentation
Solomon Gates | William K. Grefe | Jay Michael Heidbreder | Jeremy Kolpak
Overview of Project Objective
Primary GoalAchieve accurate and precise motion of laser
pointer directed at a locator beacon
Secondary GoalObtain precise object position from sensor input
Original Design Specifications Object tracking velocity:
Object velocity of 10 mph Pan/Tilt velocity of 10 radians per second Object acquisition within 1 second
Distance to object: ½ft – 20ft Range of motion:
Pan range of 180° Tilt range of 90°
Target Acquisition Accuracy ½” at a range of 20 ft (0.0021 radians) 1/8” at a range of 6” (.021 radians)
Tracking Moving Object ± 1” @ 20 ft (0.004 radians) ± ¼” @ 6” (0.041 radians)
Controller Design Process
Simulate DesiredMotors
Simulate Plant(Linearized System)
Designed PID Controllers
Tested System(Real World)
Designed Friction Compensation
Designing a Suitable Controller
Linearized our simulated plant system Estimated desired dampening and natural
frequency values to achieve a suitable overshoot and settling time.
Created a PID controller Simulated the PID controller input response
with the linearized plant system.
Real World Plant/Controller Testing
Initially our real world system did not react to the controller as the simulated system. Real World friction compensation was initially
non-existant (identify viscous and coulomb friction)
Simulated plant friction model was incorrect Estimated system models were not completely
accurate causing phase difference in system response
Pan Comparison
Pan Comparison
Tilt Comparison
Tilt Comparison
Basic Friction Compensation System
Add coulomb compensation based on the change in encoder reading
This type of compensation can fail when the motor approaches the steady state value (stiction zone)
If at this point the encoder reading does not change, the coulomb compensation is not added and the motor does not move and for future readings the encoder will not change.
Basic Friction Point to Point Video
Group 3 Friction Compensation System
Add coulomb compensation based on the difference between the current and desired position.
This will provide constant compensation until the controller acquires the desired position.
This can however cause oscillations for small movement and near the steady state value.
We fixed this by adding a dead zone to remove oscillations near steady state.
Pan Point to Point Accuracy(Point to Point Video)
Tilt Point to Point Accuracy
Pan Motion Testing(Show Motion Tracking Video)
Pan Motion Testing (Zoom)
Tilt Motion Testing
Tilt Motion Testing (Zoom)
Sensor DesignBeacon will be built from six ultrasonic transceivers
to allow 360° rangeThree receivers received signal
Sensor Problems
Radio frequency transmitter and receiver pair proved too complicated to implement on ARCS system
Ultrasonic transmitter and receivers were built and tested; devices shown to communicate with each other
No time remained to integrate transmitter with PIC microcontroller and MATLAB code with enough accuracy.
Position Acquisition
Receivers built and tested to acquire a signal from the transmitter
MATLAB code used to calculate x,y,z position based upon simulated distance information from three simulated receivers
Position was then related to the given position of laser to generate angle values
MATLABTriangulation Routine
MATLABAngle Localization
RoutineController
Da,Db,Dc
x,y,z
Θ1,Θ2
Performance Comparison
- Original Design Final SystemTracking Velocity 10 rad/sec 12.5 rad/secRange of Motion 180 pan, 90 tilt 180 pan, 90 tilt
Random Path Accuracy
0.5” @ 20 ft0.25” @ 6”
0.59” @ 20ft.03” @ 6”
Target Acquisition Accuracy
0.5” @ 20ft0.125” @ 6”
.59” @ 20ft.03” @ 6”
Acquisition Time 1 second ~0.4 seconds
Success & Challenges
It was challenging to relate the real world plant to the simulated model. We were able to achieve this in the end.
Creating the friction compensation was more of a challenge than we had expected, and in the end came up with a new way to handle this. This new system however, had its own drawbacks that we overcame.
Creating a sensor system from scratch. We were able to successfully create the components however time did not permit us to integrate and test them with our controller.