TechTonic Tuesday Presentation for Nevada County Tech Connection by ACME Robotics

1. ACME Robotics
We do robot stuff
A Presentation for Nevada
County Tech Connection

2. 2017 - 2018 Team

3. FIRST: For Inspiration and Recognition of Science
and Technology

4. FTC: First Tech Challenge

8. What is Computer Vision?
● “Gaining high-level understanding from digital images or videos”
● Includes video tracking, object recognition, 3D pose estimation, motion
estimation, and image restoration.
● We’re mainly concerned with object recognition
Acquire ActThink
Computer Vision

9. Motivation
● Robot localization (estimating the robot’s
position on the field) is very useful in
autonomous
○ Dead reckoning approaches are only accurate
for short movements
○ Other advanced sensing techniques are not
feasible (e.g., lidar is illegal)
● Major field elements are composed of
simple shapes with solid, saturated
colors
○ This makes simple image processing feasible
(i.e., no CNNs needed)

10. Image Representation
● Computers use matrices to
represent image data
● Grayscale images are stored as a
2D matrix with each cell storing the
intensity of the corresponding pixel
● Color images have multiple
channels (e.g., RGB) with a separate
matrix for each channel
● For example, the red channel matrix
stores the intensity of red in each
pixel
0
255
8-bit
gray
palette
RGB channels

11. OpenCV
● An open source computer vision (CV) and
machine learning software library
● Very common in industry
● Provides implementations of many CV algorithms
and supporting data structures
● These operations can be assembled and
composed together to form pipelines

12. Basic Example: Jewel Vision
● Jewel detection is a useful task in
this year’s game
● Although a color sensor can be used,
they are somewhat unreliable and
difficult to position
● Since the position of the jewels is
fixed, we know beforehand where the
jewels will be located
● With this insight, jewel detection is as
simple as comparing the sum of the
red/blue pixels in these regions

13. Blurring
● A pretty common operation
outside of computer vision
for editing images in general
● Blurring is also common in
image processing to smooth
out images and remove noise

14. Thresholding
● Thresholding turns a grayscale image into a binary one
● Simple procedure: pixels below the threshold become black, pixels above the
threshold become white
● RGB thresholding applies the operation to each channel separately

15. Alternative Color Space: HSV
● Alternate way to represent color
● Three channels/dimensions:
○ Hue
○ Saturation
○ Value
● Often used instead of RGB for
color thresholding

16. Binary Morphology
Dilate
Erode Close (Dilate ⇒ Erode)
Open (Erode ⇒ Dilate)

17. Contours
● Basically boundary curves
● OpenCV can find the
contours that enclose
regions in a binary image
● Allows for the pipeline to
extract useful information
from the image data

18. Example: Basic Cryptobox Vision
Original Blur HSV Threshold
ContoursFinal Binary Morphology

19. Motion Control
● Speed + Accuracy
● Lots of subsystems
need motion control
○ Drive base
○ Jewel arm
○ Dump bed
○ Dump lift
○ Relic claw
Acquire ActThink

20. Control Systems
● Get from state A to B
● Maintain a setpoint
● Various applications
○ Motion
○ Temperature
○ Chemical processes
○ Power supply

21. Basic Example
Bang-Bang control
Target: 72℉
If temp is under target, heat
Otherwise, do nothing
Overshoot
Oscillation

22. PID
Account for current error
● Slow down as it nears the target
Account for past error
● Compensate for constant forces
● Gravity, Friction, Heat loss
Account for future error
● Dampening
● Prevents overshoot

23. Motion Profiling
● Observe constraints
○ Max Velocity
○ Max Acceleration
● Time optimal
● Feedforward vs Feedback

24. Simple Algorithm
● Acceleration limited
● 3 segments
○ Acceleration
○ Cruise
○ Deceleration
Calculate
max
Velocity
Determine
Accel/Decel
Distance
Calculate
Cruise
Distance
Calculate
duration for
segments

25. Jerk Control
● Jerk - the derivative of acceleration
○ The rate at which
acceleration is changing
● Acceleration Control necessitates
infinite jerk
● 7 segments with constant jerk

26. Putting it all together
● Feed forward control - applies
control in a pre-defined way
● Feedback control - applies
control in response to the state
of a system
● V and A terms - relate desired
motor performance to voltage
applied
● Lower PID gains - feed forward
ensures that there is relatively
low error

27. Follow Our Progress
● Website: goacmerobotics.com
● Facebook: fb.com/acmeroboticsinc
● Instagram: @acmerobotics
Contact Us
● Email: goacmerobotics@gmail.com
Learn More About FIRST
● Website: firstinspires.org
Robot Code
● GitHub: https://github.com/acmerobotics/relic-recovery

28. Program Future