Open Source Autonomous Vehicle Controller

Mon, 07 Nov 2022 10:15:56 -0700

The OSAVC is a vehicle-agnostic open source hardware and software project. This project is designed to provide a real-time hardware controller adaptable to any vehicle type, suitable for aerial, terrestrial, marine, or extraterrestrial vehicles. It allows control researchers to develop state estimation algorithms, sensor calibration algorithms, and vehicle control models in a modular fashion such that once the hardware set has been developed switching algorithms requires only modifying one C function and recompiling.

Lead mentor: Aaron Hunter

Projects for the OSAVC:

Vehicle/Craft sensor driver development

Topics: Driver code to integrate sensor to a microcontroller
Skills: C, I2C, SPI, UART interfaces
Size 175 hours
Difficulty Medium
Mentor Aaron Hunter

Help develop a sensor library for use in autonomnous vehicles. Possible sensors include range finders, ping sensors, IMUs, GPS receivers, RC receivers, barometers, air speed sensors, etc. Code will be written in C using state machine methodology and non-blocking algorithms. Test the drivers on a Microchip microncontroller.

Path finding algorithm using OpenCV and machine learning

Topics: Computer vision, blob detection
Skills: C/Python, OpenCV
Size 175 or 350 hours
Difficulty Medium
Mentor Aaron Hunter

Use OpenCV to identify a track for an autonomous vehicle to follow. Build on previous work by developing a new model using EfficientDet and an existing training set of images. Port the model to TFlite and implement on the Coral USB Accelerator. Evaluate its performance against our previous efforts.

State estimation/sensor fusion algorithm development

Topics: Kalman filtering, Mahoney
Skills: C/Python, Matlab/Simulink, numerical optimization algorithms
Size 350 hours
Difficulty Challenging
Mentor Aaron Hunter

Implement an optimal state estimation algorithm from a model. This model can be derived from a Kalman filter or some other state estimation filter (e.g., Mahoney filter). THe model takes sensor readings as input and provides an estimate of the state of a vehicle. Finally, convert the model to standard C using the Simulink code generation or implement in Python (for use on a single board computer, e.g., Raspberry Pi)

Open Source Autonomous Vehicle Controller

Mon, 07 Nov 2022 10:15:56 -0700

Lead mentor: Aaron Hunter

Projects for the OSAVC:

Vehicle/Craft sensor driver development

Topics: Driver code to integrate sensor to a microcontroller
Skills: C, I2C, SPI, UART interfaces
Size 175 hours
Difficulty Medium
Mentor Aaron Hunter, Carlos Espinosa, Pavlo Vlastos

Help develop sensor libraries for use in autonomous vehicles. We are in particular interested in sensors for UAVs: airspeed sensors (pitot tube) or barometers, but also proximity detectors (ultrasonic), and range sensors. Code will be written in C using state machine methodology and non-blocking algorithms. Test the drivers on a Microchip microncontroller.

Technical Documentation

Topics: Documentation
Skills: Technical writing, markdown language, website
Size 175 hours
Difficulty Medium
Mentor Aaron Hunter/Carlos Espinosa/Pavlo Vlastos
Contributor(s) Aniruddha Thakre

Technical Documentation: Write a tutorial to demonstrate how to start with an OSAVC and program it with the robotic equivalent of HelloWorld, moving onto more sophisticated applications. Create a web page interface to the OSAVC repo highlighting this tutorial. In this project you will start from scratch with an OSAVC PCB and bring it to life, while documenting it in a way to help new users.

ROS/Gazebo Robot Simulation

Topics: Robot simulation with ROS/Gazebo
Skills ROS/Gazebo, Python
Size 175 or 350 hours
Difficulty Medium to Hard
Mentor Aaron Hunter, Carlos Espinosa, Pavlo Vlastos
Contributor(s) Damodar Datta Kancharla

Generate a simulated world and a quadcopter model in ROS/Gazebo. Provide a link from Mavlink to ROS using the mavros package and simulate a real vehicle data stream to command the simulated quadcopter in Gazebo. At the same time return the image stream from Gazebo to allow for offline processing of ML models on the images.

autonomous vehicles | UCSC OSPO

Open Source Autonomous Vehicle Controller

Vehicle/Craft sensor driver development

Path finding algorithm using OpenCV and machine learning

State estimation/sensor fusion algorithm development

Open Source Autonomous Vehicle Controller

Vehicle/Craft sensor driver development

Technical Documentation

ROS/Gazebo Robot Simulation