Design, develop, and integrate a search and rescue (SAR) system that utilizes autonomous drones and an AI-powered ground control station running on NVIDIA Jetson hardware. The system uses multi-agent intelligence for mission planning, perception, and autonomous control in field-deployable operations.
Design, develop, and integrate a search and rescue (SAR) system that utilizes autonomous drones and an AI-powered ground control station running on NVIDIA Jetson hardware. The system uses multi-agent intelligence for mission planning, perception, and autonomous control in field-deployable operations. Focus Area: Path Planning & Search Logic Sponsor: Lockheed Martin (Joseph Rivera, Systems Engineer)
Tech Stack: Python • MAVLink • PostgreSQL • PostGIS • LangGraph • YOLO • Jetson
Demonstrated MAVLink-based communication between Jetson ground station and drone.; Generated autonomous mission waypoints through multi-agent collaboration.; Delivered a fully integrated GUI interface linking AI reasoning, terrain mapping, and flight control.
Develop spatial data ingestion pipeline using OpenStreetMap and PostGIS for terrain awareness.; Implement efficient path planning algorithms that respect drone constraints, terrain, and real-time telemetry.; Design coverage search patterns for multi-UAV coordination and obstacle avoidance.; Integrate geospatial visualization into GUI for operator situational awareness.
Operator selects mission type (simulation vs live); Connects to MAVLink drone swarm; Defines Ground Control Station (GCS) location; Draws search polygon and generates terrain grid; Agent D (Mapping & Planning) generates optimized waypoints; Autonomous mission execution with live GUI feedback