Search Results for "drones"
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Showing 8 open source projects for "drones"
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CarlaAir
Fly Drones Inside a CARLA World
CarlaAir is an open-source robotics simulator that combines CARLA urban driving with multirotor drone flight inside one Unreal Engine environment. It is designed for research involving coordinated aerial and ground autonomous systems. Vehicles, pedestrians, drones, weather, and sensor streams can coexist within the same simulated world. Users can access both CARLA and AirSim-style Python APIs to control different agents and environments. The platform supports synchronized cameras, lidar, navigation sensors, trajectory recording, and joint air-ground scenarios. ROS 2 examples connect simulated vehicles and drones to external robotics workflows and RViz. ... -
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QGroundControl
Cross-platform ground control station for drones
QGroundControl is a cross-platform ground control station for MAVLink-enabled drones and autonomous vehicles. It provides full setup, configuration, flight control, and mission planning for platforms including PX4 and ArduPilot. Mission tools can create waypoint, survey, and structure-scan routes. The live flight view combines maps, instruments, vehicle position, telemetry, and optional video streams. Guided setup tools cover sensors, radios, flight modes, power systems, and vehicle parameters. ... -
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ODM
A command line toolkit to generate maps, point clouds, 3D models
OpenDroneMap ODM is a command-line photogrammetry toolkit for converting aerial imagery into geospatial and 3D products. It can process photographs captured by drones, balloons, kites, and other aerial platforms. Outputs include classified point clouds, textured 3D models, georeferenced orthophotos, and digital elevation models. The processing pipeline integrates specialized open-source projects for reconstruction, meshing, geospatial conversion, and point-cloud processing. ODM runs on Windows, macOS, and Linux and is commonly deployed through Docker. ... -
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DroneBridge for ESP32
Secure & transparent telemetry link with support for WiFi and ESP-NOW
DroneBridge for ESP32 is lightweight firmware that turns inexpensive ESP32 boards into wireless telemetry links for drones and other vehicles. It bridges serial data to standard Wi-Fi, Wi-Fi Long Range, ESP-NOW, or Bluetooth Low Energy. MAVLink, MSP, LTM, and arbitrary serial payloads can be transported through the system. Standard Wi-Fi can reach roughly 150 meters, while compatible ESP-NOW or long-range Wi-Fi setups can extend much farther. Traffic can be encrypted with AES-256-GCM, including broadcast-based ESP-NOW communication. ... -
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PilottAI
Python framework for building scalable multi-agent systems
pilottai is an AI-based autonomous drone navigation system utilizing reinforcement learning for real-time decision-making. It is designed for simulating and training drones to fly safely through dynamic environments using AI-based controllers. -
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DroneSploit
Drone pentesting framework console
DroneSploit is a Python command-line framework for authorized security testing of drones and related wireless systems. Its interface is modeled after Metasploit to provide a familiar module-oriented workflow for security researchers. The framework gathers drone-specific assessment techniques and security modules in one console. Individual modules activate only when their required external tools and dependencies are available. -
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gym-pybullet-drones
PyBullet Gymnasium environments for multi-agent reinforcement
Gym-PyBullet-Drones is an open-source Gym-compatible environment for training and evaluating reinforcement learning agents on drone control and swarm robotics tasks. It leverages the PyBullet physics engine to simulate quadrotors and provides a platform for studying control, navigation, and coordination of single and multiple drones in 3D space. -
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GAAS
GAAS is an open-source program designed for fully autonomous VTOL
GAAS, or Generalized Autonomy Aviation System, is an open-source autonomy framework for drones, VTOL aircraft, and experimental flying-car research. It focuses on robust autonomous navigation using lidar rather than relying primarily on vision. The system includes mapping, HD-map localization, path planning, obstacle handling, and aircraft-control modules. Localization components include NDT and ICP approaches, with GPU acceleration available for selected algorithms.
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