Guidance of robot arms using depth data from RGB-D camera

Image Based Visual Servoing (IBVS) is a robotic control scheme based on vision. This scheme uses only the visual information obtained from a camera to guide a robot from any robot pose to a desired one. However, IBVS requires the estimation of different parameters that cannot be obtained directly from the image. These parameters range from the intrinsic camera parameters (which can be obtained from a previous camera calibration), to the measured distance on the optical axis between the camera and visual features, it is the depth. This paper presents a comparative study of the performance of D-IBVS estimating the depth from three different ways using a low cost RGB-D sensor like Kinect. The visual servoing system has been developed over ROS (Robot Operating System), which is a meta-operating system for robots. The experiments prove that the computation of the depth value for each visual feature improves the system performance.

Light capsules shaped by curvilinear meta-surfaces

We propose a simple yet efficient method for generating in-plane hollow beams with a nearly full circular light shell without the contribution of backward propagating waves. The method relies on modulating the phase in the near field of a centrosymmetric optical wave front, such as that from a high-numerical-aperture focused wave field. We illustrate how beam acceleration may be carried out by using an ultranarrow non-flat meta-surface formed by engineered plasmonic nanoslits. A mirror-symmetric, with respect to the optical axis, circular caustic surface is numerically demonstrated that can be used as an optical bottle.