...
Optionally, you can also create new branches if you want to be more organized. You can search for git branch information online.
Submission and pull request
“LGTM” - Every pull request ever (LGTM is an initialism for Looks Good To Me)
Once your submission is ready for review, open a pull request (PR) from your fork to the WARG repository.
...
Navigate to WARG’s copy of the repository: https://github.com/UWARG/autonomy-bootcamp-2023
...
At the top, click Pull requests.
...
To the right, click the green New pull request button.
...
Under Compare changes, click the “compare across forks” link.
...
The 3rd from the left: Click the head repository dropdown and select your repository (you can search for your username).
...
The 4th from the left: Click the compare dropdown and select the branch you want to submit.
Do not open more than 1 pull request! The branch you select should contain (or eventually contain) all tasks which will be reviewed.
Once you have an open PR, you can keep updating the same branch as you get feedback. You do not need to open another PR.
...
Click on the green Create pull request button.
...
Windows Subsystem for Linux (WSL)
We do not recommend using WSL at this time because of several environment issues. You are free to make the attempt if you’re willing to encounter them (and if you solve them, please tell us). All Autonomy projects are currently cross platform so using Windows is perfectly fine.
CUDA issues:
If you have a CUDA capable GPU, you may encounter this error: Can't initialize NVML in torch/cuda/__init__.py:497
The current workaround is to hide the GPU: export CUDA_VISIBLE_DEVICES=-1
MobaXterm display issues:
If you are using MobaXterm, we suggest using a different display server. MobaXterm's display window flashes and moves towards the bottom right as OpenCV redraws the image.
This issue does not occur with a different display server: Xming version 6.9.0.31 (most recent we could find) and running: export DISPLAY=:0
This may not be necessary depending on whether you have WSLg already.
Submission and pull request
“LGTM” - Every pull request ever (LGTM is an initialism for Looks Good To Me)
Once your submission is ready for review, open a pull request (PR) from your fork to the WARG repository.
Navigate to WARG’s copy of the repository: https://github.com/UWARG/autonomy-bootcamp-2023
At the top, click Pull requests.
To the right, click the green New pull request button.
Under Compare changes, click the “compare across forks” link.
The 3rd from the left: Click the head repository dropdown and select your repository (you can search for your username).
The 4th from the left: Click the compare dropdown and select the branch you want to submit.
Do not open more than 1 pull request! The branch you select should contain (or eventually contain) all tasks which will be reviewed.
Once you have an open PR, you can keep updating the same branch as you get feedback. You do not need to open another PR.
Click on the green Create pull request button.
Once you have an open PR and are ready for review, go to your Discord bootcamp thread and send this message:
@Autonomy Lead My PR for the bootcamp is ready: [link to your PR on GitHub]The Autonomy Leads and/or bootcamp maintainers will review your PR (a message will be sent on Discord, and the comments will be on GitHub).
Read the feedback and go back to development. If any of the feedback is unclear or confusing, don’t hesitate to ask for clarification (make sure to send a message on Discord as well for visibility (e.g.
I'm not sure what you meant about [topic] on line [n]).
Tasks
Hi WARG Bootcamper,
Welcome to the team. I've taken the liberty of compiling some starter tasks to get you up to speed. They should be pretty easy to complete. Feel free to reach out if you have any questions.
Brian S. Smith, Ph.D.
Senior Manager, Software Development
AutoBots
...
| Info |
|---|
I don’t know what to do! I have no idea what’s going on! When you get stuck, the 1st first thing to do is to find documentation and examples. Then, experiment! Use the debugger and print statements to figure out what’s going on. If you’re still stuck, then reach out for help, bringing the information of what you tried and what worked/didn’t work. Independence and problem solving skills are important for the Autonomy subteam, as members are students volunteering their limited time, and often themselves don’t know either. That being said, we don’t expect you to know everything about the system from day 1, so asking questions is expected. |
...
From the repository root, try running python -m modules.bootcamp.tests.run_decision_example . It should take about 12.5 seconds wall clock time for the drone to complete its 1st first command (it will be obvious when it does). If the simulator is running too slowly, try increasing the time step size in modules/bootcamp/tests/run_decision_example.py (reducing the FPS). Take a look at modules/bootcamp/decision_example.py as well.
...
| Note |
|---|
Hints:
|
...