Poster Abstract: Hybrid and Adaptive Drone Identification through Motion Actuation and Vision Feature Matching

Unmanned aerial vehicle (UAV) swarms provide situation awareness in tasks such as emergency response, search and rescue, etc. However, most of these scenarios take place in GPS-denied environments, where accurately localizing each UAV is challenging. Heterogeneous UAV swarms, in which only a subset of the drones carry cameras, face the additional challenge of identifying each individual UAV to avoid sending position updates to the wrong drone, thus crashing. This work presents an identification mechanism based on the correlation between motion observed from external camera, and acceleration measured on each UAV's accelerometer.