U8glib V2 library for Arduino

Open source hardware and software platform to build a small scale self driving car.

A build-it-yourself, 6-wheel rover based on the rovers on Mars!

An Arduino library for BLE Serial/UART using ArduinoBLE.

PyTorch implementation for the paper "Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving"

A free sports API written for python

CircuitPython module for interacting with the VL53L0X distance sensor.

Closed-form Continuous-time Neural Networks

The device was created to measure training parameters in powerlifting - speed and displacement using an accelerometer and gyroscope - IMU.

WEB controller application for Donkey Car.

A YAML driven driver script as an alternative to the standard manage.py script to run a Donkeycar.

Using TF Lite for Object Detection experiments on a Raspberry Pi Model 3.

ROS hardware driver for UART-controlled hoverboard

ROS project for Robaka - mobile ROS testbed

Based on Sentdex's "GAN Theft Auto", but using AOgmaNeo instead of a GAN

Python wrapper class for HMC5883L magnetometer (using smbus I2c)

Ogma - EOgmaDrive https://ogma.ai/

Code used to train an augmented auto-encoder (aka denoising auto-encoder with more augmentations) for the DonkeyCar simulator.

Python library for parsing the NMEA 0183 protocol (GPS)

Implementation of reinforcement learning approach to make a car learn to drive smoothly in minutes

A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.

Python package for the qwiic system.

Arduino and Desktop compatible fast online/incremental machine learning system.

Python bindings to AOgmaNeo

Docs for donkeycar

Bluetooth Audio ALSA Backend

OpenAI gym environment for donkeycar simulator

Prebuilt binary with Tensorflow Lite enabled. For RaspberryPi / Jetson Nano. Support for custom operations in MediaPipe. XNNPACK, XNNPACK Multi-Threads, FlexDelegate.

code and data for ML-teachco-9070

TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.