Dynamic Image-Based Visual Servo Control For An Aerial Robot: Theory and Experiments

Abstract

This article considers the question of dynamic image-based visual servo control for a vertical take-off and landing unmanned aerial vehicle. The visual targets considered are colored blobs on a flat surface to which the normal direction is known. A fully nonlinear adaptive control design coupled with an asymptotic filter is provided that ensures the stability of the closed-loop system in a large domain. The image features used are a modified first order spherical moment for position regulation and optic flow for velocity damping.

Dynamic visual servoing with image moments for an unmanned aerial vehicle using a virtual spring approach

“…This motion was assumed to be constant or remained within a bounded region. [10,12,14] Section 2 models a UAV with fixed propellers and Section 3 briefly explains the image moments and the interaction matrices. [16] Section 4 discusses the feature of the feedback and proposes the controller.…”

“…Therefore, an optical flow was introduced to eliminate the sensing of the translational velocity. [13,14] These existing IBVS approaches guarantee the convergence of the position of UAVs. However, the control of the orientation around the yaw axis required additional controllers or guaranteed the boundedness of the orientation.…”

Visual servoing for underactuated VTOL UAVs: a linear, homography-based framework

“…Assume that p c D 0. Then, (13) shows the rationale behind the definition of N e k -at first order, components N e k 1 , N e k 2 , N e k 3 contain information on the translation vector p only, whereas components N e k 4 , N e k 5 , N e k 6 contain decoupled information on the orientation (i.e., L ‚ is diagonal), corrupted by components of the translation vector. This cascade structure is instrumental in the forthcoming control design and analysis.…”

Image-based visual servo control for circular trajectories for a fixed-wing aircraft

“…The term RΨ brings the measured quantity into the inertial frame while the constant scaling matrix is necessary to prove (8). Tedious but straightforward calculations show that [15] …”

“…This is due to masking and jamming effects. For these reasons, there has been considerable interest recently in the development of airborne vision systems to provide robust relative pose information that can be used instead of the GPS signals in navigation algorithms, see for examples, automated landing [7], indoor autonomous flights [8] or ground target tracking [9]. Using an airborne camera as the primary sensor for relative position tracking an observed target leads to a visual servo control problem [10], [11].…”