# Vision

Computer Vision allows your robots to understand their environment. For the competition, this is used to locate markers. It will give you information about the type of the marker, the distance/angle to the marker, etc.

# Python

To look for markers call see():

markers = R.see()

print(markers)

markers is a Python list of "marker objects", which each look like the following:

[arena Marker 0: 0.856m @0.754 degrees
{
  info.type = POTATO
  info.id = 15
  info.owning_team = ARENA
  dist = 0.856
  bearing.y = 0.754
  bearing.x = 1.03e+02
  rotation.y = 5.1
  rotation.x = -11.4
  rotation.z = 9.47
  info = TOO BIG TO PRINT
  detection = TOO BIG TO PRINT
}
]

Full reference of the properties are further below but some useful properties are:

# Codes

Every april tag has a code:

• April tags 0-39 will be used for cubes. Although only 20 are used in each round, there are another 20 spare in case some get damaged.

• April tags 100+ will around the arena on the walls. See the rules for specifics on where around the rules they will be placed

• You do not need to use the marker numbers, and can instead use marker.type and marker.owning_team

# Blockly

Blocks for vision can be found in the Vision section.

Here's an example of a Blockly program that does some basic vision:

# Example

After reading the motors documentation you should be able to create a function which moves your robot by a number of meters as well as turn. We can then use this to write some code where a robot:

• Looks for a marker

• If it can see a marker:

  • Turn so that it is facing the marker
  • Drive the distance to the marker

• If there is no marker in sight turn a bit and look again, maybe there is a marker out of view.

import robot

R = robot.Robot()

def move(distance):
    """The robot drives `distance` meters forwards"""
    print("PUT YOUR MOVE CODE HERE")

def turn(rotation):
    """The robot turns `rotation` degrees"""
    print("PUT YOUR TURN CODE HERE")

while True:
    for marker in R.see():
        turn(marker.bearing.y)  # Face the marker
        move(marker.dist)       # Drive to the marker
    else:
        turn(20)  # The robot didn't see anything and so we turn and maybe see
                  # another marker

# The Marker object

Details about the markers can be accessed using the following syntax:

markers = R.see()  # returns list of markers which the robot can see

for marker in markers:
    print(marker.dist)       # The distance to the marker in meters
    print(marker.bearing.y)  # The rotation the robot would need to turn to
                             # face the marker
    print(marker.info.id)  # The number of the marker
else:
    print("The robot didn't see any markers and skipped the for loop!")

A Marker object contains information about a detected marker. It has the following attributes:

import robot

R = robot.Robot()

markers = R.see()

for marker in markers:
    if marker.info.owner == robot.MARKER_OWNER.ARENA:
        print(f"Marker {marker.info.id} is owned by the arena")
    elif marker.info.owning_team == R.zone:
        print(f"I own {marker.info.id}")
    else:
        print(f"Marker {marker.info.id} is owned by {marker.info.owning_team}")

# The Camera object

An interface to the camera is provided incase you want to do additional computer vision.

# Changing the resolution

By default the camera takes pictures at a resolution of 640x480px. You can change this by setting the res parameter.

import robot

R = robot.Robot()

print(f"The current res is set to {R.camera.res}")
R.camera.res = (1920, 1440)
print(f"The current res is set to {R.camera.res}")

You must use one of the following resolutions:

• (640, 480) (default)
• (1296, 736)
• (1296, 976)
• (1920, 1088)
• (1920, 1440)

# Get data straight from the camera

If you wish to do your own computer vision you can capture frames directly from the camera using robot.camera.capture().

import robot

R = robot.Robot()

image = R.camera.capture()

image.grey_frame # A 2d numpy array of the image data uint8
image.colour_frame # A 3d numpy array of the image data
image.colour_type # The encoding method used to store the colour_frame defaults to 8 bit RGB.
image.time # A `datetime` object representing approximately the capture time.

# Using USB cameras

The built-in Pi Camera inside your brain should be great for your robot, however if you would like to use your own USB Camera (perhaps you want to put a camera somewhere else on your robot), you can!

USB cameras can have slightly different functionality than the built-in Pi Camera, so they'll need some fine tuning before you can use them. The basic steps outlined below should get you up and running.

Please turn your robot off before plugging in your USB Camera of choice.

To use a USB camera you will need to initialize the Robot with something which inherits from robot.vision.Camera. Then just call R.see() as you would normally.

import robot
from robot.vision import RoboConUSBCamera

R = robot.Robot(camera=RoboConUSBCamera)

print(R.see())

# Setting the resolution

You may now wish to change the resolution of your camera, this can be done the same as before with R.camera.res = (width,height).

For example, to set a USB Camera's resolution to 800x600:

import robot
from robot.vision import RoboConUSBCamera

R = robot.Robot(camera=RoboConUSBCamera)

R.camera.res = (800, 600)
print(R.see())

# Calibrating the camera

You will then need to calibrate your USB camera as the distance that it reports will not be accurate. You can do this by changing the value in the R.camera.focal_lengths dictionary up or down. By default, the robot will use the focal lengths for a "Logitech C270" camera, it's unlikely this is your camera - so see the steps below on how to calibrate it.

• Place a marker exactly 1m away from the camera (measure this distance). Make sure there are no other markers in sight of the camera.
• Copy and paste the following code into your editor. Please set the resolution value to a resolution you wish to use.

import robot
from robot.vision import RoboConUSBCamera
R = robot.Robot(camera=RoboConUSBCamera)

resolution = (640, 480)

R.camera.focal_lengths[resolution] = (120, 120) # set the focal lengths to a known bad value
R.camera.res = resolution # set resolution

marker = R.see()[0] # get first marker
d = marker.dist
focal_length = 120 / d # focal length = focal length / distance
print("Focal length is around:",focal_length)
print("Use this in your code to set the correct focal length: R.camera.focal_lengths[resolution] = ("+str(focal_length)+", "+str(focal_length)+")")

It's worth noting that this is only an average value.

The code above will output a focal length value which you should use before setting R.camera.res or R.see(). You can also copy the line of code it produces and paste that into your code to set the focal lengths.

For example, if your focal length was 123 at the resolution of 800x600, you should use the following lines of code, in the same order:

import robot
from robot.vision import RoboConUSBCamera
R = robot.Robot(camera=RoboConUSBCamera)

R.camera.focal_lengths[resolution] = (123, 123)
R.camera.res = resolution

marker = R.see()[0]