======Google Summer of Code 2025: Automotive Grade Linux projects======

[[:gsoc:google-summer-code-2025|Main GSoC Linux Foundation page: How to apply, deadlines, other workgroups, ...]]

===== Automotive Grade Linux Introduction =====
What is Automotive Grade Linux?

Automotive Grade Linux is a collaborative open source project that is bringing together automakers, suppliers and technology companies to accelerate the development and adoption of a fully open software stack for the connected car. With Linux at its core, AGL is developing an open platform from the ground up that can serve as the de facto industry standard to enable rapid development of new features and technologies.


===== AGL Community =====

Website - www.automotivelinux.org

Wiki – http://wiki.automotivelinux.org
     - https://lf-automotivelinux.atlassian.net/wiki/spaces/HOME/

Documentation (including getting started guide): https://docs.automotivelinux.org/en/master/# 

Git - gerrit.automotivelinux.org

Mailing Lists  - http://lists.automotivelinux.org/ 

Discord Server - https://discord.gg/ZztCaVeQVG - Prospective students should use #google-summer-of-code to introduce themselves. 


Code Licenses: mostly Apache 2.0, MIT for own code, otherwise as upstream

Primary Mentor contact: jsmoeller (at) linuxfoundation (dot) org


GSoC 2025 intro presentation: https://docs.google.com/presentation/d/1eo4Veo5b7HkNgRnL1MWfZcXNj89Hh5RdeBDSBf6bEaQ 


===== Project Proposals =====


==== Task #1 (large/350h):   Extend AGL's demo control panel ====

The AGL demo control panel is a pyQt (qml) application that is able to
control the AGL demo homescreen. It can replay can messages.

Task: Extend the demo control panel to drive more signals and exercise more advanced features in AGL.

Level of difficulty: intermediate

Requirements: QT, pyQT, QML, grpc, kuksa.val

Contact: jsmoeller (at) linuxfoundation.org


==== Task #2 (large/350h): Extend AGL's speech recognition app (Flutter app) with AI features====

The AGL speech recognition app is a Flutter app that uses a speech recognition engine (vosk/whisper + intent engine) for the audio processing. 

Task: Extend the demo using AI models to allow more complex interactions and reactions. Requirement is to use open-source technologies.

Level of difficulty: intermediate

Requirements: python, flutter+dart

Contact: jsmoeller (at) linuxfoundation.org


==== Task #3 (large/350h): meta-ros ====

Task: Work on meta-ros integration. (Robotic framework). Goal is a demo image integrating ROS + AGL .

Level of difficulty: intermediate/difficult

Requirements: python, ...

Contact: jsmoeller (at) linuxfoundation.org

==== Task #4 YOUR OWN IDEA ====

Bring your own idea to extend the project.

Level of difficulty: tbd

Requirements: tbd

Contact: jsmoeller (at) linuxfoundation.org