This paper presents an algorithm and the implementation of a motor schema to aid the visual localization subsystem of the ongoing EMILY project at Texas A and M University. The EMILY project aims to team an Unmanned Surface Vehicle (USV) with an Unmanned Aerial Vehicle (UAV) to augment the search and rescue of marine casualties during an emergency response phase. The USV is designed to serve as a flotation device once it reaches the victims. A live video feed from the UAV is provided to the casuality responders giving them a visual estimate of the USVs orientation and position to help with its navigation. One of the challenges involved with casualty response using a USV UAV team is to simultaneously control the USV and track it. In this paper, we present an implemented solution to automate the UAV camera movements to keep the USV in view at all times. The motor schema proposed, uses the USVs coordinates from the visual localization subsystem to control the UAVs camera movements and track the USV with minimal camera movements such that the USV is always in the cameras field of view.
@cite_1: Firstly, the characteristics of UAV visual tracking system were analysed, secondly the three-dimensional oculomotor control system model of biomimetic eye was developed based on the oculomotor neural paths. Then a new UAV visual tracking system was established. The on-board pan-tilt camera control system based on biomimetic eye can compensate the deflection caused by the UAV rotation and the movement of ground relative to the UAV. The pan-tilt camera can simulate human eye movements including smooth pursuit, VOR and OKR, and the control pattern of camera motor is velocity control, thus it can track the ground moving target continuously, smoothly, clearly and stably like human eye. Finally the experimental results were presented.
A camera-control approach by UAV was proposed in @cite_1 , where the UAV camera movements are based on a biomimetic eye based control, being able to simulate the human eye movements resulting in stable and smooth camera movements. The algorithm is computationally heavy, which is not suitable for our purposes.