OODA Sense: A Geography-Informed Multi-Agent Search and Rescue Drone Algorithm

Autonomous search and rescue drones are an emerging tool for detecting survivors in a range of disaster conditions. While many current approaches use the same searching tactics regardless of energy availability, visibility, and hazards, our algorithm uses the OODA framework (Observe, Orient, Decide, Act) to dynamically adjust to different constraints. In our simulation, the drones communicate with each other, combining knowledge of local geography and rescue-time hazard detection to plan each drone's optimal route.
Interns: Eshaan Sombhatta, Tanvi Anand

Mentor: Claire Hong (FPS/KVG)