Dynamic Data-Driven Motion Planning and Control for Pervasive Situational Awareness Application Systems

Distributed Autonomous System Laboratory

Collaborators and Students: 

AFOSR, Dynamic Data Driven Application Systems Program,

collaborator: Sertac Karaman, MIT

Project Description: 

Summary: Many modern Air Force missions take place in uncertain and dynamic environments, where a predictive model of the battlefield is essential to make effective decisions. These models are driven by data acquired using mobile sensors, such as optical and infrared cameras on board Unmanned Aerial Vehicles (UAVs). However, due to the enormous production costs and the presence of destructive adversarial behavior, it is impractical to deploy UAVs in large numbers. The emerging Unattended Ground Sensor (UGS) technology holds the potential to revolutionize Air Force operations in highly dynamic environments. UGSs can be produced cheaply and deployed in massive numbers. They can house seismic, acoustic, infrared, and optical sensors. However, the UGS may not have sufficient power to communicate their data to a central processing hub, necessitating data-ferrying with UAVs. This project seeks utilize and contribute to the develop Dynamic Data Driven Application System framework for developing UAV based data ferrying algorithms to facilitate battlespace picture development and situational awareness.