This code is the result of the collaboration of RL Turkey team.

Multi-Agent Deep Recurrent Q-Learning with Bayesian epsilon-greedy on AirSim simulator

Reinforcement learning for an AirSim quadrotor implemented in Unity

An autonomous drone racing system integrating vision-guided trajectory adjustments with MPC for planar control and PID for elevation. Real-time visual feedback refines gate localization and trajectory generation, ensuring efficient and accurate navigation.

Deep Q-learning in AirSim quadrotor environment.

Drone navigation and obstacle avoidance by deep reinforcement learning and transfer learning (IN PROCESS)

Wi-Fi6 Collision avoidance simulator for Microsoft AirSim

These are two Interfaces to fly drones in AirSim simulator.

A 3d cloud mesh is generated from a, set of photos taken from a drone, in airsim environment.

Controlling Vehicles with ROS1_bridge and ROS2 on Ubuntu 20.04 - AirSim Simulation Environment

Entrenament d’un model de IA en un entorn virtual per a la seva aplicació en la extinció d’incendis forestals: Prova de concepte - Universitat Oberta de Catalunya - Treball Final de Grau

Based on the data generated from FRCNN test, this program shows how the drone will fly according to it.

Self driving car with Deep Q-Learning

Python scripts that flies a drone in AirSim environment and generates data.