Robust visual servoing in 3d reaching tasks

This paper describes a novel approach to the problem of reaching an object in space under visual guidance. The approach is characterized by a great robustness to calibration errors, such that virtually no calibration is required. Servoing is based on binocular vision: a continuous measure of the end-effector motion field, derived from real-time computation of the binocular optical flow over the stereo images, is compared with the actual position of the target and the relative error in the end-effector trajectory is continuously corrected. The paper outlines the general framework of the approach, shows how visual measures are obtained and discusses the synthesis of the controller along with its stability analysis. Real-time experiments are presented to show the applicability of the approach in real 3-D applications

A Variational Stereo Method for the Three-Dimensional Reconstruction of Ocean Waves

We develop a novel remote sensing technique for the observation of waves on the ocean surface. Our method infers the 3-D waveform and radiance of oceanic sea states via a variational stereo imagery formulation. In this setting, the shape and radiance of the wave surface are given by minimizers of a composite energy functional that combines a photometric matching term along with regularization terms involving the smoothness of the unknowns. The desired ocean surface shape and radiance are the solution of a system of coupled partial differential equations derived from the optimality conditions of the energy functional. The proposed method is naturally extended to study the spatiotemporal dynamics of ocean waves and applied to three sets of stereo video data. Statistical and spectral analysis are carried out. Our results provide evidence that the observed omnidirectional wavenumber spectrum S(k) decays as k-2.5 is in agreement with Zakharov's theory (1999). Furthermore, the 3-D spectrum of the reconstructed wave surface is exploited to estimate wave dispersion and currents

Self-calibration technique for on-machine spindle-mounted vision systems

On-machine measuring (OMM) systems are being more and more applied in machine tools in order to measure workpieces on the machine itself. Many of these systems are directly mounted in the machine spindle, so the measuring uncertainty is affected by clamping positioning and orientation variations, especially when integrating optical systems based on machine vision. This paper presents a self-calibration technique for vision systems by using redundant information of on machine measurements, avoiding extra mechanical anchoring or calibration means. It has been applied to a vision system with the angular placement uncertainty of a tool holder coupling being the main uncertainty contributor. A milling machine pilot case has been selected for demonstration, showing an effective self-calibration capability both in laboratory and industrial conditions

Cooperative monocular-based SLAM for multi-UAV systems in GPS-denied environments

This work presents a cooperative monocular-based SLAM approach for multi-UAV systems that can operate in GPS-denied environments. The main contribution of the work is to show that, using visual information obtained from monocular cameras mounted onboard aerial vehicles flying in formation, the observability properties of the whole system are improved. This fact is especially notorious when compared with other related visual SLAM configurations. In order to improve the observability properties, some measurements of the relative distance between the UAVs are included in the system. These relative distances are also obtained from visual information. The proposed approach is theoretically validated by means of a nonlinear observability analysis. Furthermore, an extensive set of computer simulations is presented in order to validate the proposed approach. The numerical simulation results show that the proposed system is able to provide a good position and orientation estimation of the aerial vehicles flying in formation.Peer ReviewedPostprint (published version

Current, emerging and future technologies for sensing the environment

This paper reviews current technologies that are used for environmental monitoring, and presents emerging technologies that will dramatically improve our ability to obtain spatially distributed, real-time data about key indicators of environmental quality at specific locations. Futuristic approaches to environmental monitoring that employ fundamental breakthroughs in materials science to revolutionise the way we monitor our environment will also be considered. In particular, approaches employing biomimetic and 'adaptive'/'stimuli-responsive' materials will be highlighted, as these could play an important role in the realization of small, low power, low cost, autonomous sensing and communications platforms that could form the building blocks of the much vaunted environmental 'sensor web'