Vision‐only control and guidance for aircraft

Abstract

An unmanned aerial vehicle usually carries an array of sensors whose output is used to estimate vehicle attitude, velocity, and position. This paper details the development of guidance, navigation, and control strategies for a glider, which is capable of flying a terminal trajectory to a known fixed object using only a single vision sensor. Controlling an aircraft using only vision presents two unique challenges: First, absolute state measurements are not available from a single image; and second, the images must be collected and processed at a high rate to achieve the desired controller performance. The image processor utilizes an integral image representation and a rejective cascade filter to find and classify simple features in the images, reducing the image to the most probable pixel location of the destination object. Then, an extended Kalman filter uses measurements obtained from a single image to estimate the states that would otherwise be unobservable in a single image. In this research, the flights are constrained to keep the destination object in view. The approach is validated through simulation. Finally, experimental data from autonomous flights of a glider, instrumented only with a single nose-mounted camera, intercepting a target window during short low-level flights, are presented.

Vision-Based Tracking of Uncooperative Targets

“…In this paper, we consider the specific problem of navigating (following) a target object (leader) using a single vision camera. One of the earliest problems addressed was the estimation, control, and guidance of a glider [1,2] towards a target window opening, after launch, in order to deliver a simple payload. The only sensor available on the glider was a single camera.…”

Visual Servoing of Quadrotor Micro-Air Vehicle Using Color-Based Tracking Algorithm

“…Integral image for tracking has been applied in by Proctor et. al (9) in their research of small plane relying only on vision as sensor. We combine our vision strategy with a model-based non-linear controller (13) to hover the MAV on the selected target.…”

A vision-based approach for high accuracy assessment of satellite attitude

“…[23]. Nevertheless, when vision-based only systems are used, often the accuracy needed (and provided) is of the order of degrees or few decimal of degrees [1]. Usually, in this application field there is no need to go deep into the sources of error of the software system in order to attain a higher accuracy, simply because what achieved is suitable for the application itself.…”

“…It is worth remarking that our approach is the first attempt to exploit the Earth as a native target to be tracked in a satellite navigation system, using an on-board monocular camera to recover the satellite attitude. Also, our method only relies on "corner" points naturally present in the image and does not require any prior knowledge of specific targets to be tracked (like in [1]). …”