3D Real-Time Reconstruction using the Cloud

This work presents a 3D real-time reconstruction based on a visual SLAM (Simultaneous Localization and Mapping) approach using a RGBD camera. The proposed system aims to create a 3D model of an environment using a low-power computer and Amazon EC2 (Elastic Compute Cloud) server for computation offloading

ORB-SLAM: A Versatile and Accurate Monocular SLAM System

This paper presents ORB-SLAM, a feature-based monocular simultaneous localization and mapping (SLAM) system that operates in real time, in small and large indoor and outdoor environments. The system is robust to severe motion clutter, allows wide baseline loop closing and relocalization, and includes full automatic initialization. Building on excellent algorithms of recent years, we designed from scratch a novel system that uses the same features for all SLAM tasks: tracking, mapping, relocalization, and loop closing. A survival of the fittest strategy that selects the points and keyframes of the reconstruction leads to excellent robustness and generates a compact and trackable map that only grows if the scene content changes, allowing lifelong operation. We present an exhaustive evaluation in 27 sequences from the most popular datasets. ORB-SLAM achieves unprecedented performance with respect to other state-of-the-art monocular SLAM approaches. For the benefit of the community, we make the source code public

Estimación Simultánea de Escenas Deformables y Trayectoria a partir de una Secuencia de Imágenes Monoculares

Durante la última década se ha demostrado experimentalmente la posibilidad de realizarreconstrucciones 3D de entornos desconocidos tomando como único dato la secuencia deimágenes que toma una cámara que se mueve con una trayectoria también desconocida. Estosmétodos son conocidos como SLAM (Simultaneous Localization And Mapping). Dichossistemas, asumen que la escena observada es rígida, una hipótesis razonable en ambientesrobóticos, tales como interiores de edificios, entornos urbanos y en menor medida entornosexteriores. Sin embargo, dicha hipótesis no se cumple en otras situciones, como por ejemplo,en las escenas médicas de cirugía con endoscopio, en las que los sistemas actuales fallarían.Para abandonar la hipótesis de rigidez, en este trabajo se combinan las ecuaciones de Navierpara sólidos deformables, con un EKF (Extended Kalman Filter) para estimar mediante unprocesamiento secuencial, la estructura 3D no rígida y el movimiento de la cámara a partir deuna secuencia de imágenes monoculares. Las ecuaciones de Navier se resuelvennuméricamente mediante el MEF (método de los elementos finitos). Para ello, la estructuraobservada es discretizada mediante una malla de elementos planos triangulares cuyos nodosse corresponden con los puntos característicos medidos. La metodología es validadaexperimentalmente utilizando secuencias de imágenes reales de escenas deformables ymovimientos de cámara realistas. La propuesta es particularmente relevante para eltratamiento de secuencias médicas adquiridas con endoscopio, permitiendo incorporar larespuesta mecánica de los tejidos ante la aplicación de diferentes acciones

In-situ Mechanical Characterization of Abdominal Muscle Using Stereo Imaging

We present a method to characterize in vivo the mechanical behavior of abdominal muscle, using inverse finite element analysis and image processing algorithms to estimate the properties. The aim of this technique is to help surgeon to choose the hernia mesh that better reproduces the mechanical behavior of the healthy muscle

Sensor Influence in the Performance of Simultaneous Mobile Robot Localization and Map Building

Mobile robot navigation in unknown environments requires the concurrent estimation of the mobile robot localization with respect to a base reference and the construction of a global map of the navigation area. In this paper we present a comparative study of the performance of the localization and map building processes using two distinct sensorial systems: a rotating 2D laser rangefinder, and a trinocular stereo vision system

RoboEarth

Humans can use the Internet to share knowledge and to help each other accomplish complex tasks. Until now, robots have not taken advantage of this opportunity. Sharing knowledge between robots requires methods to effectively encode, exchange, and reuse data. In this article, we present the design and first implementation of a system for sharing knowledge between robots

Creating and using RioboEarth object models

This paper presented an approach to create 3D object models for robotic and vision applications in a fast and inexpensive way compared to established approaches. By using the RoboEarth system for storing the created object models users have world-wide access to the data and can immediately reuse a model as soon as it was created and uploaded. The approach shows general applicability for different kinds of cameras. In this work this was shown by two example implementations for the recognition process of objects. The quality of the recognition can be verified in the video. Combined with the knowledge saved in the RoboEarth database the objects can also be properly classifie