Skip to content

The assignment 3 for the course Autonomous Vehicles at University of Montreal

Notifications You must be signed in to change notification settings

AHHHZ975/lx-computer-vision

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

11 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Duckietown Logo

**Learning Experience (LX): Computer Vision **

You can watch:

1- The qualitative results of lane detection and lane following experiments on the real Duckiebot here.

2- The qualitative results of lane detection and lane following experiments on the virtual Duckiebot in the Duckiematrix environment here.

Instructions

NOTE: All commands below are intended to be executed from the root directory of this exercise (i.e., the directory containing this README).

1. Make sure your exercise is up-to-date

Update your exercise definition and instructions,

git pull upstream ente

NOTE: to pull from upstream, you need to have completed the instructions in the duckietown-lx repository README to fork this repository.

2. Make sure your system is up-to-date

This exercise is meant to be run with the ente version of the shell commands. You can switch to that version with dts profile switch ente.

  • 💻 Update the shell commands: dts update

  • 💻 Update your laptop/desktop: dts desktop update

  • 🚙 Update your Duckiebot: dts duckiebot update ROBOTNAME (where ROBOTNAME is the name of your (real or virtual - more on this later) Duckiebot chosen during the initialization procedure.)

3. Work on the exercise

Launch the code editor

Open the code editor by running the following command,

dts code editor

Wait for a URL to appear on the terminal, then click on it or copy-paste it in the address bar of your browser to access the code editor. The first thing you will see in the code editor is this same document, you can continue there.

Walkthrough of notebooks

NOTE: You should be reading this from inside the code editor in your browser.

Inside the code editor, use the navigator sidebar on the left-hand side to navigate to the notebooks directory and open the first notebook.

Follow the instructions on the notebook and work through the notebooks in sequence.

Building your code

You can build your code with

dts code build -R ROBOT_NAME

This will build a docker image with your code compiled inside - you should your ROS node get built during the process.

Testing with Duckiematrix

In order to test your code in the Duckiematrix you will need a virtual robot. You can create one with the command:

dts duckiebot virtual create [VIRTUAL_ROBOT_NAME]

where [VIRTUAL_ROBOT_NAME] can be anything you like (but remember it for later).

Then you can start your virtual robot with the command:

dts duckiebot virtual start [VIRTUAL_ROBOT_NAME]

You should see it with a status Booting and finally Ready if you look at dts fleet discover:

     | Hardware |   Type    | Model |  Status  | Hostname 
---  | -------- | --------- | ----- | -------- | ---------
vbot |  virtual | duckiebot | DB21J |  Ready   | vbot.local

Now that your virtual robot is ready you can start the Duckiematrix. From this exercise directory do:

dts code start_matrix

You should see the Unity-based Duckiematrix simulator start up.

💻 Testing

To test your code in the duckiematrix you can do:

dts code workbench -m -R [VIRTUAL_ROBOT_NAME]

and to test your code on your real Duckiebot you can do:

dts code workbench -R [ROBOT_NAME]

In another terminal, you can launch the noVNC viewer for this exercise which can be useful to send commands to the robot and view the odometry that you calculating in the RViZ window.

dts code vnc -R [ROBOT_NAME]

where [ROBOT_NAME] could be the real or the virtual robot (use whichever you ran the dts code workbench and dts code build command with).

In the noVNC desktop, click on the icon marked "VLS - Visual Lane Servoing Exercise" and then you should follw the prompts in the terminal where you ran dts code workbench.

Now you can proceed to the first notebook.

About

The assignment 3 for the course Autonomous Vehicles at University of Montreal

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 99.7%
  • Other 0.3%