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Program Quarky Mecanum Robot with PictoBlox and Python
[Mecanum]

Programming the Quarky Mecanum with Python in PictoBlox

Description
In this lesson, learn how to program the Quarky Mecanum robot with PictoBlox and Python in both Stage and Upload modes. Understand the functions provided in the Quarky Mecanum library, and see how to control the robot’s motors, pick-and-place robot, and gripper robot.

PictoBlox also provides the ability to program the Quarky Mecanum using Python in Desktop / Laptop versions. Let’s see how you can do it in this lesson.

PictoBlox

With PictoBlox, you can program the Quarky Mecanum!

If you haven’t installed PictoBlox, please follow the instructions:


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enablebox()
The function enables the automatic display of the landmark on pose/hand detected on the stage.
Syntax: enablebox()
disablebox()
The function disables the automatic display of the landmark on pose/hand detected on the stage.
Syntax: disablebox()
analysestage()
This function is used to analyze the image received as input from the stage, for human pose detection.
Syntax: analysestage()
x()
This function returns the x position of the pose landmark detected. The position is mapped with the stage coordinates.
Syntax: x(landmark_number = 1, pose_number = 1)
y()
This function returns the y position of the pose landmark detected. The position is mapped with the stage coordinates.
Syntax: y(landmark_number = 1, pose_number = 1)
isdetected()
The function tells whether the human pose is detected or not.
Syntax: isdetected(landmark_number = 1, pose_number = 1)
analysehand()
This function is used to analyze the image received as input from the camera, for human hand detection.
Syntax: analysehand()
ishanddetected()
The function tells whether the human hand is detected or not.
Syntax: ishanddetected()
gethandposition()
This function returns the specified parameter of the hand landmark detected.
Syntax: gethandposition(parameter = 1, landmark_number = 4)
handx()
This function returns the x position of the hand detected. The position is mapped with the stage coordinates.
Syntax: handx()
handy()
This function returns the y position of the hand detected. The position is mapped with the stage coordinates.
Syntax: handy()
pushdata()
The function adds the specified text data to the specified class.
Syntax: pushdata(text_data = “your text”, class_label = “class”)
train()
The function trains the NLP model with the data added with pushdata() function.
Syntax: train()
reset()
The function resets and clears the NLP model.
Syntax: reset()
analyse()
The function analyses the specified test and provides the class name under which it has been classified by the NLP model.
Syntax: analyse(text = “your text”)
video()
The function is used to control the state of the camera.
Syntax: video(video_state = “on”, transparency = 1)
enablebox()
The function enables the automatic display of the box on object detection on the stage.
Syntax: enablebox()
disablebox()
The function disables the automatic display of the box on object detection on the stage.
Syntax: disablebox()
setthreshold()
This function is used to set the threshold for the confidence (accuracy) of object detection, 0 being low confidence and 1 being high confidence.
Syntax: setthreshold(threshold = 0.5)
analysecamera()
This function is used to analyze the image received as input from the camera, for objects.
Syntax: analysecamera()
analysestage()
This function is used to analyze the image received as input from the stage, for objects.
Syntax: analysestage()
count()
This function returns the total number of objects detected in the camera feed or the stage.
Syntax: count()
classname()
This function is used to get the class name of the analyzed object.
Syntax: classname(object = 1)
x()
This function returns the x position of the object detected. You can specify the object for which the value is needed. The position is mapped with the stage coordinates.
Syntax: x(object = 1)
y()
This function returns the y position of the object detected. You can specify the object for which the value is needed. The position is mapped with the stage coordinates.
Syntax: y(object = 1)
width()
This function returns the width of the object detected. You can specify the object for which the value is needed. The position is mapped with the stage coordinates.
Syntax: width(object = 1)
height()
This function returns the height of the object detected. You can specify the object for which the value is needed. The position is mapped with the stage coordinates.
Syntax: height(object = 1)
confidence()
This function is used to get the confidence (accuracy) of object detection, 0 being low confidence and 1 being high confidence.
Syntax: confidence(object = 1)
issignaldetected()
The function returns whether the specified signal is detected in the analysis or not.
Syntax: issignaldetected(signal_name = “Go”)
getsignaldetail()
The function returns the specified parameter for the specified signal detected.
Syntax: getsignaldetail(signal_name = “Go”, parameter_value = 1)
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Connecting Quarky with PictoBlox

Let’s begin by first connecting Quarky to PictoBlox. Follow the steps below for connecting Quarky to PictoBlox:

    1. First, connect Quarky to your laptop using a USB cable.
    2. Next, open PictoBlox on your desktop.
    3. After that, select Python Coding as your coding environment.
    4. Then, click the Board button in the toolbar and select Board as Quarky.
    5. Next, select the appropriate Serial port if the Quarky is connected via USB or the Bluetooth Port if you want to connect Quarky via Bluetooth and press Connect.
      COM Port
    6. Click on the Upload Firmware button. This will upload the latest firmware in Quarky.
      Note: If your device already has the latest firmware, then PictoBlox will show the message – Firmware is already updated. For learning more you can refer to this tutorial: https://ai.thestempedia.com/docs/quarky/quarky-toubleshooting/updating-quarky-firmaware-with-pictoblox/
    7. Once the firmware is uploaded, Quarky starts the Getting Started program. This runs only for the first time. Run through it.

And voila! Quarky is now connected to PictoBlox.

Quarky Mecanum Python Library for Stage Mode

Stage mode is one of the two modes you can write your programs in PictoBlox. In this mode, you can write scripts for the sprite and boards to interact with sprites in real-time. If you disconnect the board with PictoBlox, you cannot interact with the board anymore.

You can toggle between the upload mode and stage mode using the button on the top right side of PictoBlox.

In Python, use the following object declaration to use Python functions in Stage Mode:

meca = Mecanum(1, 2, 7, 8)

Quarky Mecanum Python Library for Upload Mode

Upload mode allows you to write scripts and upload them to the board so that you can use them even when it is not connected to your computer, for example, you need to upload a script for making moving robots. In this case, Quarky will run offline according to the program and it cannot interact with the stage.

In Python, use the following object declaration to use Python functions in Upload Mode:

from quarky import *
from expansion_addon import Mecanum
meca = Mecanum(1, 2, 7, 8)

Python Functions

The following functions are available for use in the Quarky Mecanum library:


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enablebox()
The function enables the automatic display of the landmark on pose/hand detected on the stage.
Syntax: enablebox()
disablebox()
The function disables the automatic display of the landmark on pose/hand detected on the stage.
Syntax: disablebox()
analysestage()
This function is used to analyze the image received as input from the stage, for human pose detection.
Syntax: analysestage()
x()
This function returns the x position of the pose landmark detected. The position is mapped with the stage coordinates.
Syntax: x(landmark_number = 1, pose_number = 1)
y()
This function returns the y position of the pose landmark detected. The position is mapped with the stage coordinates.
Syntax: y(landmark_number = 1, pose_number = 1)
isdetected()
The function tells whether the human pose is detected or not.
Syntax: isdetected(landmark_number = 1, pose_number = 1)
analysehand()
This function is used to analyze the image received as input from the camera, for human hand detection.
Syntax: analysehand()
ishanddetected()
The function tells whether the human hand is detected or not.
Syntax: ishanddetected()
gethandposition()
This function returns the specified parameter of the hand landmark detected.
Syntax: gethandposition(parameter = 1, landmark_number = 4)
handx()
This function returns the x position of the hand detected. The position is mapped with the stage coordinates.
Syntax: handx()
handy()
This function returns the y position of the hand detected. The position is mapped with the stage coordinates.
Syntax: handy()
pushdata()
The function adds the specified text data to the specified class.
Syntax: pushdata(text_data = “your text”, class_label = “class”)
train()
The function trains the NLP model with the data added with pushdata() function.
Syntax: train()
reset()
The function resets and clears the NLP model.
Syntax: reset()
analyse()
The function analyses the specified test and provides the class name under which it has been classified by the NLP model.
Syntax: analyse(text = “your text”)
video()
The function is used to control the state of the camera.
Syntax: video(video_state = “on”, transparency = 1)
enablebox()
The function enables the automatic display of the box on object detection on the stage.
Syntax: enablebox()
disablebox()
The function disables the automatic display of the box on object detection on the stage.
Syntax: disablebox()
setthreshold()
This function is used to set the threshold for the confidence (accuracy) of object detection, 0 being low confidence and 1 being high confidence.
Syntax: setthreshold(threshold = 0.5)
analysecamera()
This function is used to analyze the image received as input from the camera, for objects.
Syntax: analysecamera()
analysestage()
This function is used to analyze the image received as input from the stage, for objects.
Syntax: analysestage()
count()
This function returns the total number of objects detected in the camera feed or the stage.
Syntax: count()
classname()
This function is used to get the class name of the analyzed object.
Syntax: classname(object = 1)
x()
This function returns the x position of the object detected. You can specify the object for which the value is needed. The position is mapped with the stage coordinates.
Syntax: x(object = 1)
y()
This function returns the y position of the object detected. You can specify the object for which the value is needed. The position is mapped with the stage coordinates.
Syntax: y(object = 1)
width()
This function returns the width of the object detected. You can specify the object for which the value is needed. The position is mapped with the stage coordinates.
Syntax: width(object = 1)
height()
This function returns the height of the object detected. You can specify the object for which the value is needed. The position is mapped with the stage coordinates.
Syntax: height(object = 1)
confidence()
This function is used to get the confidence (accuracy) of object detection, 0 being low confidence and 1 being high confidence.
Syntax: confidence(object = 1)
issignaldetected()
The function returns whether the specified signal is detected in the analysis or not.
Syntax: issignaldetected(signal_name = “Go”)
getsignaldetail()
The function returns the specified parameter for the specified signal detected.
Syntax: getsignaldetail(signal_name = “Go”, parameter_value = 1)
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Conclusion

In conclusion, PictoBlox is a powerful coding environment that allows you to program the Quarky Mecanum Robot with Python in both Stage and Upload modes. The Quarky Mecanum library provides several functions that can be used to control the robot’s motors, pick–and–place robot, and gripper robot. With the help of PictoBlox, you can easily program and control the Quarky Mecanum robot!

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