drone-simulation

Multicopter UAV simulation for control/RL experiments.

Multi-agent drone swarm simulation framework built on PyBullet for robotics and reinforcement learning.

This repository provides a tutorial on setting up and simulating multiple drones using ROS 2, ArduPilot, and Gazebo Harmonic. It includes installation steps, required configurations, launch files, and example scenarios to help you build and test a multi-drone simulation environment.

This contain a drone simulated in V-REP (CoppeliaSim)

A lightweight Python-based 3D network multi-agent simulator. Uses a cell-based congestion model. Calculates risk, loudness and battery capacities of the agents. Suitable for 3D network optimization tasks.

NSER-IBVS: Numerically Stable Efficient Reduced Image-Based Visual Servoing with knowledge distillation for autonomous drone control and navigation in GPS-denied environments. ICCV 2025

A Unity-based quadrotor simulation for AI training, reinforcement learning, and autonomous drone navigation. Features realistic flight physics, ML-Agents integration and Python support.

Learn drone autonomy from simulation to real flight: ROS2 Humble, ArduPilot SITL, Gazebo Harmonic, MAVROS, Raspberry Pi companion computer. Step-by-step beginner tutorials, hardware-verified.

High performance drone simulation environment for ultra efficient simulation of the drone's PoV. Can also be used to benchmark machine learning models.

UAVLnQ: An Architecture for Security Analysis of Cyber-Physical Network Behavior in UAV Swarms

ArduGazeboSim is a comprehensive Docker-based simulation environment for ArduPilot and Gazebo Classic 11, designed for drone development and testing. This project provides a complete containerized setup with ROS Noetic, allowing developers to work seamlessly across different machines without worrying about dependencies.

🚁 Fly-in — A Python drone routing and simulation system focused on graph algorithms, pathfinding, scheduling, and optimization.

Modern drone control station

Simulation of drone navigation through a procedurally generated disaster environment in CoppeliaSim. Features a quadcopter equipped with an RGB-D camera, manual keyboard or RC joystick control and dynamic obstacle generation for AI-based navigation and dataset collection.

A 3D autonomous drone simulation with AI-powered flight capabilities using deep reinforcement learning. Features realistic physics, LiDAR obstacle detection, and a neural network that learns to navigate complex environments through both reinforcement learning and imitation learning from human demonstrations.

Tools and background services to use quadcopter sims in hardware-in-the-loop simulation

Fly-in is a graph-based drone routing simulator that uses capacity-aware pathfinding and real-time Pygame visualization.

A sanitized, open-source sample template of the Nongin Aerial Wings Aid Ground Control System (NAWA GCS). Simulates real-time dual-drone disaster response (Scout & Delivery), telemetry overlay, automatic sequential supply dispatch, and ground-reloading in a fully offline client-side React sandbox.

Open-source multi-project 3D geospatial and digital twin platform powered by CesiumJS, Three.js, React, and Go, with real-time UAV trajectory visualization.

Prototype of a digital twin for Crazyflies