Project Vision
VFF-Nav addresses the fundamental challenge of autonomous obstacle avoidance for UAVs using a Virtual Force Field (VFF) approach. The algorithm creates attractive forces toward goals and repulsive forces from obstacles, enabling real-time navigation in complex environments.
Key Features
- Real-time autonomous navigation and obstacle avoidance in dynamic environments
- Seamless integration with ROS 2 and Gazebo simulation environment
- Full compatibility with PX4 autopilot for real-world deployment
- Heuristic parameter optimization for optimal force field performance
- Electrostatic analogy model providing intuitive physical interpretation
- Robust collision avoidance using sonar-based obstacle detection
Technical Architecture
The VFF-Nav system is built on a modular architecture with three core components:
ROS 2/Gazebo Simulator
Provides the virtual environment and dynamic model of the PX4 drone for comprehensive testing and validation.
Parameter Optimization Module
Heuristically explores the VFF parameter space using a genetic programming to identify optimal configurations for different scenarios.
VFF-Nav Controller
Implements the force field algorithm for reactive navigation and real-time obstacle avoidance.
Applications
The VFF-Nav system is designed for various real-world applications including:
- Infrastructure inspection and monitoring
- Search and rescue operations
- Agricultural monitoring and precision farming
- Environmental data collection
- Security and surveillance
- Delivery and logistics in complex environments