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

RIDI: Robust IMU Double Integration

This paper proposes a novel data-driven approach for inertial navigation, which learns to estimate trajectories of natural human motions just from an inertial measurement unit (IMU) in every smartphone. The key observation is that human motions are repetitive and consist of a few major modes (e.g., standing, walking, or turning). Our algorithm regresses a velocity vector from the history of linear accelerations and angular velocities, then corrects low-frequency bias in the linear accelerations, which are integrated twice to estimate positions. We have acquired training data with ground-truth motions across multiple human subjects and multiple phone placements (e.g., in a bag or a hand). The qualitatively and quantitatively evaluations have demonstrated that our algorithm has surprisingly shown comparable results to full Visual Inertial navigation. To our knowledge, this paper is the first to integrate sophisticated machine learning techniques with inertial navigation, potentially opening up a new line of research in the domain of data-driven inertial navigation. We will publicly share our code and data to facilitate further research

The Role of Thermal Accumulation on the Fabrication of Diffraction Gratings in Ophthalmic PHEMA by Ultrashort Laser Direct Writing

The fabrication of diffraction gratings by ultrashort direct laser writing in poly-hydroxyethyl-methacrylate (PHEMA) polymers used as soft contact lenses is reported. Diffraction gratings were inscribed by focusing laser radiation 100 µm underneath the surface of the samples. Low- and high-repetition rate Ti:sapphire lasers with 120 fs pulsewidth working at 1 kHz and 80 MHz respectively were used to assess the role of thermal accumulation on microstructural and optical characteristics. Periodic patterns were produced for different values of repetition rate, pulse energy, laser wavelength, distance between tracks, and scanning speed. Compositional and structural modifications of the processed areas were studied by micro-Raman spectroscopy showing that under certain parameters, thermal accumulation may result in local densification. Far-field diffraction patterns were recorded for the produced gratings to assess the refractive index change induced in the processed areasThis research was funded by the PIT2 program of the University of Murcia’s own research plan. Fundación Seneca grant No 20647/JLI/18, Junta de Castilla y León (project SA287P18), MINECO (project FIS2017-87970-R) and European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie IF No 795630 are also acknowledged

QUIJOTE Scientific Results. II. Polarisation Measurements of the Microwave Emission in the Galactic molecular complexes W43 and W47 and supernova remnant W44

We present Q-U-I JOint TEnerife (QUIJOTE) intensity and polarisation maps at 10-20 GHz covering a region along the Galactic plane 24<l<45 deg, |b|<8 deg. These maps result from 210 h of data, have a sensitivity in polarisation of ~40 muK/beam and an angular resolution of ~1 deg. Our intensity data are crucial to confirm the presence of anomalous microwave emission (AME) towards the two molecular complexes W43 (22 sigma) and W47 (8 sigma). We also detect at high significance (6 sigma) AME associated with W44, the first clear detection of this emission towards a SNR. The new QUIJOTE polarisation data, in combination with WMAP, are essential to: i) Determine the spectral index of the synchrotron emission in W44, beta_sync =-0.62 +/-0.03, in good agreement with the value inferred from the intensity spectrum once a free-free component is included in the fit. ii) Trace the change in the polarisation angle associated with Faraday rotation in the direction of W44 with rotation measure -404 +/- 49 rad/m2. And iii) set upper limits on the polarisation of W43 of Pi_AME <0.39 per cent (95 per cent C.L.) from QUIJOTE 17~GHz, and <0.22 per cent from WMAP 41 GHz data, which are the most stringent constraints ever obtained on the polarisation fraction of the AME. For typical physical conditions (grain temperature and magnetic field strengths), and in the case of perfect alignment between the grains and the magnetic field, the models of electric or magnetic dipole emissions predict higher polarisation fractions.Comment: Accepted for publication in MNRA

The Lack of Structural and Dynamical Evolution of Elliptical Galaxies since z ~ 1.5: Clues from Self-Consistent Hydrodynamical Simulations

We present results of a study on the evolution of the parameters characterizing the structure and dynamics of the relaxed elliptical-like objects (ELOs) identified at z=0, z=1 and z=1.5 in a set of hydrodynamical, self-consistent simulations operating in the context of a concordance cosmological model. The values of the stellar mass, the stellar half-mass radius and the stellar mean-square velocity have been measured in each ELO and found to populate, at any z, a flattened ellipsoid close to a plane (the dynamical plane, DP). Our simulations indicate that, at the intermediate zs considered, individual ELOs evolve, increasing the values of these parameters as a consequence of on-going mass assembly, but, nevertheless, their DP is roughly preserved within its scatter, in agreement with observations of the Fundamental Plane of ellipticals at different zs. We briefly discuss how this lack of significant dynamical and structural evolution in ELO samples arises, in terms of the two different phases operating in the mass aggregation history of their dark matter halos. According with our simulations, most dissipation involved in ELO formation takes place at the early violent phase, causing the stellar mass, the stellar half-mass radius and the stellar mean-square velocity parameters to settle down to the DP, and, moreover, the transformation of most of the available gas into stars. In the subsequent slow phase, ELO stellar mass growth preferentially occurs through non-dissipative processes, so that the DP is preserved and the ELO star formation rate considerably decreases. These results hint, for the first time, to a possible way of explaining, in the context of cosmological simulations, different apparently paradoxical observational results on ellipticals.Comment: 12 pages, 1 figure. Minor changes to match the published versio

A scalable FPGA-based architecture for depth estimation in SLAM

The current state of the art of Simultaneous Localisation and Mapping, or SLAM, on low power embedded systems is about sparse localisation and mapping with low resolution results in the name of efficiency. Meanwhile, research in this field has provided many advances for information rich processing and semantic understanding, combined with high computational requirements for real-time processing. This work provides a solution to bridging this gap, in the form of a scalable SLAM-specific architecture for depth estimation for direct semi-dense SLAM. Targeting an off-the-shelf FPGA-SoC this accelerator architecture achieves a rate of more than 60 mapped frames/sec at a resolution of 640×480 achieving performance on par to a highly-optimised parallel implementation on a high-end desktop CPU with an order of magnitude improved power consumption. Furthermore, the developed architecture is combined with our previous work for the task of tracking, to form the first complete accelerator for semi-dense SLAM on FPGAs, establishing the state of the art in the area of embedded low-power systems

Integrating Simulink, OpenVX, and ROS for Model-Based Design of Embedded Vision Applications

OpenVX is increasingly gaining consensus as standard platform to develop portable, optimized and power-efficient embedded vision applications. Nevertheless, adopting OpenVX for rapid prototyping, early algorithm parametrization and validation of complex embedded applications is a very challenging task. This paper presents a comprehensive framework that integrates Simulink, OpenVX, and ROS for model-based design of embedded vision applications. The framework allows applying Matlab-Simulink for the model-based design, parametrization, and validation of computer vision applications. Then, it allows for the automatic synthesis of the application model into an OpenVX description for the hardware and constraints-aware application tuning. Finally, the methodology allows integrating the OpenVX application with Robot Operating System (ROS), which is the de-facto reference standard for developing robotic software applications. The OpenVX-ROS interface allows co-simulating and parametrizing the application by considering the actual robotic environment and the application reuse in any ROS-compliant system. Experimental results have been conducted with two real case studies: An application for digital image stabilization and the ORB descriptor for simultaneous localization and mapping (SLAM), which have been developed through Simulink and, then, automatically synthesized into OpenVX-VisionWorks code for an NVIDIA Jetson TX2 boar

Clues on Regularity in the Structure and Kinematics of Elliptical Galaxies from Self-consistent Hydrodynamical Simulations: the Dynamical Fundamental Plane

[Abridged] We have analysed the parameters characterising the mass, size and velocity dispersion both at the baryonic scale and at the halo scales of two samples of relaxed elliptical-like-objects (ELOs) identified, at z=0, in a set of self-consistent hydrodynamical simulations operating in the context of a concordance cosmological model. At the halo scale they have been found to satisfy virial relations; at the scale of the baryonic object the (logarithms of the) ELO stellar masses, projected stellar half-mass radii, and stellar central l.o.s. velocity dispersions define a flattened ellipsoid close to a plane (the intrinsic dynamical plane, IDP), tilted relative to the virial one, whose observational manifestation is the observed FP. The ELO samples have been found to show systematic trends with the mass scale in both, the relative content and the relative distributions of the baryonic and the dark mass ELO components, so that homology is broken in the spatial mass distribution (resulting in the IDP tilt), but ELOs are still a two-parameter family where the two parameters are correlated. The physical origin of these trends presumably lies in the systematic decrease, with increasing ELO mass, of the relative amount of dissipation experienced by the baryonic mass component along ELO stellar mass assembly. ELOs also show kinematical segregation, but it does not appreciably change with the mass scale. The non-homogeneous population of IDPs explains the role played by the virial mass to determine the correlations among intrinsic parameters. In this paper we also show that the central stellar line-of-sight velocity dispersion of ELOs, is a fair empirical estimator of the virial mass, and this explains the central role played by this quantity at determining the observational correlations.Comment: 20 pages, 17 Figures. Only changed to a more readable styl

Comparison of lead-acid and li-ion batteries lifetime prediction models in stand-alone photovoltaic systems

Several models for estimating the lifetimes of lead-acid and Li-ion (LiFePO4 ) batteries are analyzed and applied to a photovoltaic (PV)-battery standalone system. This kind of system usually includes a battery bank sized for 2.5 autonomy days or more. The results obtained by each model in different locations with very different average temperatures are compared. Two different locations have been considered: the Pyrenees mountains in Spain and Tindouf in Argelia. Classical battery aging models (equivalent full cycles model and rainflow cycle count model) generally used by researchers and software tools are not adequate as they overestimate the battery life in all cases. For OPzS lead-acid batteries, an advanced weighted Ah-throughput model is necessary to correctly estimate its lifetime, obtaining a battery life of roughly 12 years for the Pyrenees and around 5 years for the case Tindouf. For Li-ion batteries, both the cycle and calendar aging must be considered, obtaining more than 20 years of battery life estimation for the Pyrenees and 13 years for Tindouf. In the cases studied, the lifetime of LiFePO4 batteries is around two times the OPzS lifetime. As nowadays the cost of LiFePO4 batteries is around two times the OPzS ones, Li-ion batteries can be competitive with OPzS batteries in PV-battery standalone systems

Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving

We propose a stereo vision-based approach for tracking the camera ego-motion and 3D semantic objects in dynamic autonomous driving scenarios. Instead of directly regressing the 3D bounding box using end-to-end approaches, we propose to use the easy-to-labeled 2D detection and discrete viewpoint classification together with a light-weight semantic inference method to obtain rough 3D object measurements. Based on the object-aware-aided camera pose tracking which is robust in dynamic environments, in combination with our novel dynamic object bundle adjustment (BA) approach to fuse temporal sparse feature correspondences and the semantic 3D measurement model, we obtain 3D object pose, velocity and anchored dynamic point cloud estimation with instance accuracy and temporal consistency. The performance of our proposed method is demonstrated in diverse scenarios. Both the ego-motion estimation and object localization are compared with the state-of-of-the-art solutions.Comment: 14 pages, 9 figures, eccv201