Dark energy from scalar field with Gauss Bonnet and non-minimal kinetic coupling

We study a model of scalar field with a general non-minimal kinetic coupling to itself and to the curvature, and additional coupling to the Gauss Bonnet 4-dimensional invariant. The model presents rich cosmological dynamics and some of its solutions are analyzed. A variety of scalar fields and potentials giving rise to power-law expansion have been found. The dynamical equation of state is studied for two cases, with and without free kinetic term . In both cases phenomenologically acceptable solutions have been found. Some solutions describe essentially dark energy behavior, and and some solutions contain the decelerated and accelerated phases.Comment: 21 page

Asymmetric embedding in brane cosmology

We derive a system of cosmological equations for a braneworld with induced curvature which is a junction between several bulk spaces. The permutation symmetry of the bulk spaces is not imposed, and the values of the fundamental constants, and even the signatures of the extra dimension, may be different on different sides of the brane. We then consider the usual partial case of two asymmetric bulk spaces and derive an exact closed system of scalar equations on the brane. We apply this result to the cosmological evolution on such a brane and describe its various partial cases.Comment: 10 page

A Comparison of Monocular Visual SLAM and Visual Odometry Methods Applied to 3D Reconstruction

This work was supported by the SDAS Research Group (www.sdas-group.com accessed on 16 June 2023).Pure monocular 3D reconstruction is a complex problem that has attracted the research community's interest due to the affordability and availability of RGB sensors. SLAM, VO, and SFM are disciplines formulated to solve the 3D reconstruction problem and estimate the camera's ego-motion; so, many methods have been proposed. However, most of these methods have not been evaluated on large datasets and under various motion patterns, have not been tested under the same metrics, and most of them have not been evaluated following a taxonomy, making their comparison and selection difficult. In this research, we performed a comparison of ten publicly available SLAM and VO methods following a taxonomy, including one method for each category of the primary taxonomy, three machine-learning-based methods, and two updates of the best methods to identify the advantages and limitations of each category of the taxonomy and test whether the addition of machine learning or updates on those methods improved them significantly. Thus, we evaluated each algorithm using the TUM-Mono dataset and benchmark, and we performed an inferential statistical analysis to identify the significant differences through its metrics. The results determined that the sparse-direct methods significantly outperformed the rest of the taxonomy, and fusing them with machine learning techniques significantly enhanced the geometric-based methods' performance from different perspectives.SDAS Research Grou

Kimera-Multi: Robust, Distributed, Dense Metric-Semantic SLAM for Multi-Robot Systems

This paper presents Kimera-Multi, the first multi-robot system that (i) is robust and capable of identifying and rejecting incorrect inter and intra-robot loop closures resulting from perceptual aliasing, (ii) is fully distributed and only relies on local (peer-to-peer) communication to achieve distributed localization and mapping, and (iii) builds a globally consistent metric-semantic 3D mesh model of the environment in real-time, where faces of the mesh are annotated with semantic labels. Kimera-Multi is implemented by a team of robots equipped with visual-inertial sensors. Each robot builds a local trajectory estimate and a local mesh using Kimera. When communication is available, robots initiate a distributed place recognition and robust pose graph optimization protocol based on a novel distributed graduated non-convexity algorithm. The proposed protocol allows the robots to improve their local trajectory estimates by leveraging inter-robot loop closures while being robust to outliers. Finally, each robot uses its improved trajectory estimate to correct the local mesh using mesh deformation techniques. We demonstrate Kimera-Multi in photo-realistic simulations, SLAM benchmarking datasets, and challenging outdoor datasets collected using ground robots. Both real and simulated experiments involve long trajectories (e.g., up to 800 meters per robot). The experiments show that Kimera-Multi (i) outperforms the state of the art in terms of robustness and accuracy, (ii) achieves estimation errors comparable to a centralized SLAM system while being fully distributed, (iii) is parsimonious in terms of communication bandwidth, (iv) produces accurate metric-semantic 3D meshes, and (v) is modular and can be also used for standard 3D reconstruction (i.e., without semantic labels) or for trajectory estimation (i.e., without reconstructing a 3D mesh).Comment: Accepted by IEEE Transactions on Robotics (18 pages, 15 figures

Crisis financieras y el papel de la banca central : un enfoque teórico

Las crisis financieras tienen efectos nefastos en una economía en caso que ésta no pueda ser prevenida eficientemente por el planificador central o el agente regulador de este sector. En el manejo de las crisis es importante distinguir entre la regulación previa que se tiene que dar al sector financiero y el comportamiento de la autoridad monetaria en caso que se produzca la crisis a pesar de la regulación. Para poder ofrecer soluciones en cuanto a regulación y comportamiento de la banca central es preciso conocer cómo se manejan las instituciones financieras en su afán de conseguir captaciones y colocar las mismas para obtener utilidades; así mismo es importante conocer el comportamiento de los agregados en caso que se produzca un shock monetario que pueda llevar a la economía a una crisis bancaria, en este contexto las soluciones propuestas dependerán de las preferencias por estabilidad de determinados agregados por parte de la autoridad. No es posible entender el comportamiento de las instituciones financieras y del gobierno como ente regulador si no se considera a estos como agentes racionales que maximizan su utilidad, en este trabajo se presenta estas características y se plantea diferentes situaciones para ofrecer recomendaciones que sean compatibles con los incentivos de cada agente participante en una situación de crisis bancaria

Resilient and Distributed Multi-Robot Visual SLAM: Datasets, Experiments, and Lessons Learned

This paper revisits Kimera-Multi, a distributed multi-robot Simultaneous Localization and Mapping (SLAM) system, towards the goal of deployment in the real world. In particular, this paper has three main contributions. First, we describe improvements to Kimera-Multi to make it resilient to large-scale real-world deployments, with particular emphasis on handling intermittent and unreliable communication. Second, we collect and release challenging multi-robot benchmarking datasets obtained during live experiments conducted on the MIT campus, with accurate reference trajectories and maps for evaluation. The datasets include up to 8 robots traversing long distances (up to 8 km) and feature many challenging elements such as severe visual ambiguities (e.g., in underground tunnels and hallways), mixed indoor and outdoor trajectories with different lighting conditions, and dynamic entities (e.g., pedestrians and cars). Lastly, we evaluate the resilience of Kimera-Multi under different communication scenarios, and provide a quantitative comparison with a centralized baseline system. Based on the results from both live experiments and subsequent analysis, we discuss the strengths and weaknesses of Kimera-Multi, and suggest future directions for both algorithm and system design. We release the source code of Kimera-Multi and all datasets to facilitate further research towards the reliable real-world deployment of multi-robot SLAM systems.Comment: 8 pages, 9 figure

Observational consequences of the Standard Model Higgs inflation variants

We consider the possibility to observationally differentiate the Standard Model (SM) Higgs driven inflation with non-minimal couplingto gravity from other variants of SM Higgs inflation based on the scalar field theories with non-canonical kinetic term such as Galileon-like kinetic term and kinetic term with non-minimal derivative coupling to the Einstein tensor. In order to ensure consistent results, we study the SM Higgs inflation variants by using the same method, computing the full dynamics of the background and perturbations of the Higgs field during inflation at quantum level. Assuming that all the SM Higgs inflation variants are consistent theories, we use the MCMC technique to derive constraints on the inflationnoary parameters and the Higgs boson mass from their fit to WMAP7+SN+BAO data set. We conclude that a combination of a Higgs mass measurement by the LHC and accurate determination by the PLANCK satellite of the spectral index of curvature perturbations and tensor-to-scalar ratio will enable to distinguish among these models. We also show that the consistency relations of the SM Higgs inflation variants are distinct enough to differentiate the models.Comment: 22 pages, 4 figure