The paper proposes an off-line robot motion planning approach, aimed at the reduction of the energy consumption, for any trajectory defined on a set of target points including some "fly" ones, i.e., points that must not be exactly reached by the robot. The proposed solution is based on the search for alternative paths close to the fly target points originally defined by the operator, and on the computation of the mechanical and total energy associated to each single possible motion defined for the generated alternative paths. A branch and bound algorithm is employed to scan all the possible motions and find the complete trajectory that corresponds to the minimum energy consumption. The approach has been implemented in a software architecture that exploits some COMAU software modules, but it could be easily adapted to generic, similar modules. The results that have been experimentally obtained for two typical industrial cycles, performed by a COMAU Racer robot, can be considered as very satisfying.
A: Convolutional neural networks (CNNs) have found applications in many image processing tasks, such as feature extraction, image classification, and object recognition. It has also been shown that the inverse of CNNs, so-called deconvolutional neural networks, can be used for inverse problems such as plasma tomography. In essence, plasma tomography consists in reconstructing the 2D plasma profile on a poloidal cross-section of a fusion device, based on line-integrated measurements from multiple radiation detectors. Since the reconstruction process is computationally intensive, a deconvolutional neural network trained to produce the same results will yield a significant computational speedup, at the expense of a small error which can be assessed using different metrics. In this work, we discuss the design principles behind such networks, including the use of multiple layers, how they can be stacked, and how their dimensions can be tuned according to the number of detectors and the desired tomographic resolution for a given fusion device. We describe the application of such networks at JET and COMPASS, where at JET we use the bolometer system, and at COMPASS we use the soft X-ray diagnostic based on photodiode arrays. K : Computerized Tomography (CT) and Computed Radiography (CR); Plasma diagnostics -interferometry, spectroscopy and imaging 1Corresponding author. 2See the author list of Overview of the JET preparation for Deuterium-Tritium Operation by E. Joffrin et al. in Nucl.
Despite their popularity, occupancy grids cannot be directly applied to problems where the identity of the objects populating an environment needs to be taken into account (eg object tracking, scene interpretation, etc), in this cases it is necessary to postprocess the grid in order to extract object information.This paper approaches the problem by proposing a novel algorithm inspired on image segmentation techniques. The proposed approach works without prior knowledge about the number of objects to be detected and, at the same time, is very fast. This is possible thanks to the use of a novel Self Organizing Network (SON) coupled with a dynamic threshold. Our experimental results on both real and simulated data show that our approach is robust and able to operate at normal camera framerate.
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