An OpenaAIGym-based framework allowing to test hybrid approaches (RL + path planning) for multi-UAV systems that are supposed to provide smart services.
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Updated
Dec 19, 2023 - Python
An OpenaAIGym-based framework allowing to test hybrid approaches (RL + path planning) for multi-UAV systems that are supposed to provide smart services.
🔥🔥 CVPR 2025 (Nashville TN) - The 4th Anti-UAV Workshop & Challenge 🥉
Tutorial for Multi-UAV (Quadcopters) simulation in Gazebo and Ardupilot.
An OpenAIGym-based framework allowing to test Delay-Aware Deep Reinforcement Learning algorithms for cooperative multi-UAV systems in fully customizable scenarios (e.g., coverage maximization, tracking, spotting).
AVDC 2021 - GNC of a SWARM of UAVs in a numerical simulation by Alex Martinez and Tom Antoine
Multi-UAV Assisted Mobile Edge Computing: A hybrid optimization approach of combining multi-agent RL techniques with collaborative and adaptive caching policies for supporting mobile edge computing through UAVs.
GNC of a SWARM of UAVs in a SITL by Tom Antoine and Alex Martinez - Cranfield University AVDC MSc 2021
An implementation of multi-UAV formation control with obstacle avoidance capability. Based on the paper [Flocking for Multi-Agent Dynamic Systems: Algorithms and Theory], this project provides formation control, target tracking and visualization tools for UAV swarm simulation.
A repository of running multi-quadrotor simulations in Gazebo with PX4 inside Docker container.
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.
CookieCutter Templates for Building Custom Starling Applications
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