This paper addresses the problem of vision-based robot control where a reference image defines the equilibrium. Specifically, we consider the class of intensity-based nonmetric solutions, which provide for high accuracy, versatility, and robustness. Existing techniques within that class present either a fully coupled control error dynamics or at best only achieve decoupling of the translational part, i.e., they can only obtain a lower triangular system. These couplings in the system dynamics increase analysis complexity and may degrade system performance. This work proposes a new nonlinear observer for also decoupling the rotational part, i.e., for diagonally decoupling the entire control error dynamics. Theoretical proofs of stability and of those decoupling properties are provided. Improved performances are also experimentally confirmed using synthetic and real data, planar and nonplanar objects, simulating and applying a camera-mounted 6-DoF robotic arm.

This article addresses the problem of direct vision-based robot control where the equilibrium state is defined via a reference image. Direct methods refer to intensity-based nonmetric techniques to perform that stabilization. Intensity-based strategies provide for higher accuracy, whereas not requiring any metric information improves their versatility. However, existing direct techniques either have a coupled error dynamics, or are designed for planar objects only. This paper proposes a new direct technique that decouples the translational motion from the rotational one for the general case of both planar and nonplanar targets under general translational and rotational displacements. Furthermore, for the important case of a fronto-parallel planar object, the proposed technique leads to a fully diagonal interaction matrix. The equilibrium state is made locally exponentially stable for all those cases. These improvements are theoretically proven and experimentally demonstrated using a 6-DoF robotic arm.

On this paper, inertial orientation measurements are exploited to compensate the rotational degrees of freedom for an aerial vehicle carrying a perspective camera, taking a sequence of images of the ground plane. It is known that, on the pure translation case, full homographies are reduced to planar homologies, and the relative scene depth of two points equals the reciprocal ratio of their image distances to the the FOE. The first part of this paper covers trajectory recovery for an airship carrying a perspective camera taking a sequence of images of the ground plane, as a series of relative poses between successive camera poses. This is commonly named “Visual Odometry“. Previous results showed that the ratio of heights over the ground plane on two views can be calculated more accurately, and thus the altitude component of the trajectory, and here these results are extended by recovering the full 3D camera trajectory. In the second part, the same rotation-compensated imagery is exploited on the mapping domain: from pixel correspondences between successive images the height of points over the ground plane can be recovered, and placed on a DEM grid, performing 3D mapping from monocular aerial images. These results may be useful on the SLAM context.

Internet robotic systems have a different role in the use and development of aerial robots compared to that for ground robots. While for ground robotic vehicles, Internet is useful for remote operation or to make remote development, in aerial vehicles, in addition, the safety aspect must be considered very carefully. This paper addresses the requirements to the specific case of Internet aerial robots. It describes the conceptual and implementation aspects of an Internet-based software architecture for the AURORA unmanned autonomous airship project, showing its use in the different project phases.

Project AURORA aims at the development of an unmanned airship capable of autonomous flight over user-defined locations for aerial inspection and imagery acquisition. In this article the authors report a successful autonomous flight achieved through a set of pre-defined points, one of the first of its kind in the literature. The guidance control strategy is based on a path tracking error generation methodology that takes into account both the distance and the angular errors of the airship with respect to the desired trajectory. The control strategy uses a PI controller for the tail surfaces' deflection.

We present one of the first Internet-accessible airship simulators, based on a comprehensive airship dynamic model. The simulator is meant to be used as a tool for the development of control and navigation methods for autonomous and semi-autonomous robotic airships and as testbed for airship pilot training. Realistic views of both the airship in flight and that of a virtual pilot are provided, as are commands to apply thrust to the engines, swivel them up and down, and deflect the control surfaces. This work is significant for providing robotics researchers with means to safely experiment with airship control.