TactileGCN: A Graph Convolutional Network for Predicting Grasp Stability with Tactile Sensors

Tactile sensors provide useful contact data during the interaction with an object which can be used to accurately learn to determine the stability of a grasp. Most of the works in the literature represented tactile readings as plain feature vectors or matrix-like tactile images, using them to train machine learning models. In this work, we explore an alternative way of exploiting tactile information to predict grasp stability by leveraging graph-like representations of tactile data, which preserve the actual spatial arrangement of the sensor's taxels and their locality. In experimentation, we trained a Graph Neural Network to binary classify grasps as stable or slippery ones. To train such network and prove its predictive capabilities for the problem at hand, we captured a novel dataset of approximately 5000 three-fingered grasps across 41 objects for training and 1000 grasps with 10 unknown objects for testing. Our experiments prove that this novel approach can be effectively used to predict grasp stability

Interactive 3D object recognition pipeline on mobile GPGPU computing platforms using low-cost RGB-D sensors

We propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: The system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient-assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The resulting system is able to recognize objects in a scene in less than 7 seconds, offering an interactive frame rate and thus allowing its deployment on a mobile robotic platform. Because of that, the system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human–computer interaction systems based on visual information. A video showing the proposed system while performing online object recognition in various scenes is available on our project website (http://www.dtic.ua.es/~agarcia/3dobjrecog-jetsontk1/)

Open innovation : organizational challenges of a new paradigm of innovation management

The goal of this paper is to analyze the main problems that emerge from the open innovation model. Adopting as analytical framework an organizational perspective we divide the main challenges that arise from the management of open innovation in two main categories: coordination problems as a result of open the innovation system to ideas and knowledge that may lie outside the boundaries of the firm and, incentive problems related with the creation and value capture of ideas an knowledge by the innovator. We describe and analyze several problems related with coordination and incentives.peer-reviewe

Methodology for the metric restoration of the historical cartography applied to Francisco Coello's cartografic series of the Royal Site of Aranjuez

Hojas Kilométricas (Kilometric Sheets). Specifically, the study focuses on those sheets referring to the city centre and surrounding area of the Royal Site of Aranjuez, a town in the south of the Province of Madrid. The aim of this study is to restore the actual size and measurements of scanned images of the Hojas Kilométricas. This would allow us, among other things, to reestablish both the format and scale of the original plans. To achieve this goal it is necessary to rectify and then georeference these images, i.e. assign them a geographic reference system. This procedure is essential in the overlaying and comparison of the Hojas Kilométricas of the Royal Site with other historical cartography as well as other sources related to the same area from different time periods. Subsequent research would allow us, for example, to reconstruct the time-evolution of the urban area, to spot new construction and to pinpoint the locations of any altered or missing buildings or architectural features. In addition, this would allow us to develop and integrate databases for GIS models applicable to the management of our cultural heritage

Optimizing Scan Homogeneity for Building Full-3D Lidars based on Rotating a Multi-Beam Velodyne Rangefinder

Multi-beam lidar (MBL) scanners are compact, light, and accessible 3D sensors with high data rates, but they offer limited vertical resolution and field of view (FOV). Some recent robotics research has profited from the addition of a degree-of-freedom (DOF) to an MBL to build rotating multi-beam lidars (RMBL) that can achieve high-resolution scans with full spherical FOV. In a previous work, we offered a methodology to analyze the complex 3D scan measurement distributions produced by RMBLs with a rolling DOF and no pitching. In this paper, we investigate the effect of introducing constant pitch angles in the construction of the RMBLs with the purpose of finding a kinematic configuration that optimizes scan homogeneity with a spherical FOV. To this end, we propose a scalar index of 3D sensor homogeneity that is based on the spherical formulation of Ripley's K function. The optimization is performed for the widely used Puck (VLP-16) and HDL-32 sensors by Velodyne.This work was partially funded by the Spanish project {DPI2015-65186-R}. The publication has received support from Universidad de Málaga, Campus de Excelencia Andalucía Tech

Achieving Identity-based cryptography in a personal digital assistant

Continuous technological advances have allowed that mobile devices, such as Personal Digital Assistants (PDAs), can execute sophisticated applications that more often than not must be equipped with a layer of security that should include the confidentiality and the authentication services within its repertory. Nevertheless, when compared against front-end computing devices, most PDAs are still seen as constrained devices with limited processing and storage capabilities. In order to achieve Identity-Based Cryptography (IBC), which was an open problem proposed by Adi Shamir in 1984, Boneh and Franklin presented in Crypto 2001, a solution that uses bilinear pairings as its main building block. Since then, IBC has become an active area of investigation where many efficient IBC security protocols are proposed year after year. In this paper, we present a cryptographic application that allows the secure exchange of documents from a Personal Digital Assistant (PDA) that is wirelessly connected to other nodes. The architecture of our application is inspired by the traditional PGP (Pretty Good Privacy) email security protocol. Our application achieves identity-based authentication and confidentiality functionalities at the 80-bit security level through the usage of a cryptographic library that was coded in C++. Our library can perform basic primitives such as bilinear pairings defined over the binary field and the ternary field , as well as other required primitives known as map-to-point hash functions. We report the timings achieved by our application and we show that they compare well against other similar works published in the open literature

Multi-sensor 3D object dataset for object recognition with fullpose estimation

A new dataset for 3D object recognition using the new high-resolution Kinect V2sensor and some other popular low-cost devices like Prime Sense Carmine. Since most already existing datasets for3D object recognition lack some features such as 3D pose information about objects in the scene, per pixel segmentation or level of occlusion, we propose a new one combining all this information in a single dataset that can be used to validate existing and new 3D object recognition algorithms. Moreover, with the advent of the new KinectV2 sensor we are able to provide high-resolution data for RGB and depth information using a single sensor, whereas other datasets had to combine multiple sensors. In addition, we will also provide semiautomatic segmentation and semantic labels about the different parts of the objects so that the dataset could be used for testing robot grasping and scene labeling systems as well as for object recognitionThis work was partially funded by the Spanish Government DPI2013-40534-R Grant. This work has also been funded by the grant ‘‘Ayudas para Estudios de Máster e Iniciación a la Investigación’’ from the University of Alicante