amov-lab/Prometheus
Prometheus
Prometheus is an autonomous drone flight stack providing a software suite for navigation, target recognition, and flight control. It functions as a computer vision navigation engine and a precision autonomous landing controller, enabling unmanned aerial vehicles to operate without manual pilot input.
The system distinguishes itself through multi-vehicle coordination and swarm synchronization, allowing aerial and ground vehicles to maintain formations and execute joint maneuvers via a shared communication framework. It further integrates a simulation environment for software-in-the-loop testing, which validates flight logic and autonomous behaviors in a virtual setting before deployment to physical hardware.
The platform covers a broad range of robotics capabilities, including deep learning-based visual target tracking, depth-sensor spatial mapping for obstacle avoidance, and dynamic trajectory planning. It also implements closed-loop feedback control for precise alignment and descent during autonomous landing operations.
Features
- Navigation Engines - A system that uses depth cameras and visual target recognition to plan obstacle-free paths in real time.
- Autonomous Flight Controllers - Integrates flight control, trajectory planning, and target detection for fully autonomous drone operations.
- Robotics & Drones - Integrating flight control, trajectory planning, and target detection to operate unmanned aerial vehicles without manual pilot input.
- Computer Vision - Identifies specific objects, colors, and numbers using deep learning for real-time target recognition.
- Deep Learning Pipelines - Implements a deep learning pipeline to process camera streams for real-time visual target tracking.
- Visual Target Tracking - Uses deep learning and computer vision to identify and lock onto moving visual targets.
- Flight Feedback Controllers - Adjusts vehicle alignment and descent speed in real time using sensor-based feedback.
- Landing Controllers - Provides closed-loop control for precise autonomous landing and descent speed adjustment.
- Autonomous Landing Systems - Provides automated descent and alignment controls for precise landing on static or moving platforms.
- Path Planning Algorithms - Implements algorithms for calculating optimal flight paths through complex environments with obstacles.
- Swarm Coordination - Synchronizes multiple robotic units to maintain formations and execute collective joint maneuvers.
- Precision Landing Systems - Guiding a drone to descend and align itself accurately onto static or moving landing platforms using real-time sensor feedback.
- Multi-Vehicle Fleet Coordinators - Synchronizes the movement of multiple drones to execute joint maneuvers and maintain formations.
- 3D Spatial Mapping - Transforms depth sensor data into 3D spatial representations for autonomous obstacle avoidance.
- Flight Logic Validations - Verify onboard software components by running them in a virtual environment to validate logic before deploying to physical hardware.
- Flight Logic Simulators - Provides a software-in-the-loop simulation to validate flight logic before physical deployment.
- Flight Simulation Environments - Implements a virtualization layer to test autonomous flight control logic in a simulated environment.
- Spatial Mapping Systems - Generates 2D or 3D environmental representations using depth cameras for autonomous navigation.
- Software-in-the-Loop Simulators - Testing flight logic and onboard software in a virtual environment to ensure safety before deploying to physical hardware.
- Environmental Mapping Techniques - Creates 2D and 3D environmental occupancy maps using depth sensors for robotic spatial awareness.
- Cross-Platform Message Buses - Uses a cross-platform communication layer to synchronize state and commands across different vehicle types.
- Message Bus Interfaces - Standardizes inter-process communication and telemetry synchronization between aerial and ground vehicles.
