Monocular vision-based human following on miniature robotic blimp

Abstract

We present an approach that allows the Georgia Tech Miniature Autonomous Blimp (GT-MAB) to detect and follow a human. This accomplishment is the first Human Robot Interaction (HRI) demonstration between an uninstrumented human and a robotic blimp. GT-MAB is an ideal platform for HRI missions because it is safe to humans and can support sufficient flight time for HRI experiments. However, due to complex aerodynamic influence on the blimp, the human following task for GT-MAB with a single on-board camera is a challenging problem. We integrate Haar face detector and KLT feature tracker to achieve robust human tracking. After a human face is detected in the real-time video stream, we estimated the 3D positions of the human with respect to GT-MAB. Visionbased PID controllers are designed based on estimated relative position and the motion primitives of GT-MAB such that it can achieve stable and continuous human following behavior. Experimental results are presented to demonstrate the human following capability on GT-MAB.