arXiv subjects

Fernando Caballero

Publications and source records attributed to Fernando Caballero.

At least 37 records · Page 2Linked to original sources

arXiv2025

Interface dynamics of wet active systems

We study the roughening of interfaces in phase-separated active suspensions on substrates. At both large length and timescales, we show that the interfacial dynamics belongs to the |q|KPZ universality class discussed in Besse et al. Phys. Rev. Lett. 130, 187102 (2023). This holds despite the presence of long-ranged fluid flows. At early times, however, or for sufficiently small systems, the roughening exponents are the same as those in the presence of a momentum-conserving fluid. Surprisingly, when the effect of substrate friction can be ignored, the interface becomes random beyond a de Gennes-Taupin lengthscale which depends on the interfacial tension.

cond-mat.soft↗

arXiv2025

ARS548_ros. An ARS 548 RDI radar driver for ROS

The ARS 548 RDI Radar is a premium model of the fifth generation of 77 GHz long range radar sensors with new RF antenna arrays, which offer digital beam forming. This radar measures independently the distance, speed and angle of objects without any reflectors in one measurement cycle based on Pulse Compression with New Frequency Modulation. Unfortunately, to the best of our knowledge, there are no open source drivers available for Linux systems to enable users to analyze the data acquired by the sensor. In this paper, we present a driver that can interpret the data from the ARS 548 RDI sensor and make it available over the Robot Operating System versions 1 and 2 (ROS and ROS2). Thus, these data can be stored, represented, and analyzed using the powerful tools offered by ROS. Besides, our driver offers advanced object features provided by the sensor, such as relative estimated velocity and acceleration of each object, its orientation and angular velocity. We focus on the configuration of the sensor and the use of our driver including its filtering and representation tools. Besides, we offer a video tutorial to help in its configuration process. Finally, a dataset acquired with this sensor and an Ouster OS1-32 LiDAR sensor, to have baseline measurements, is available, so that the user can check the correctness of our driver.

cs.RO↗

arXiv2024

Active fluids form system-spanning filamentary networks

Recent experimental realizations of liquid-liquid phase separation of active liquid crystals have offered an insight into the interaction between phase separation, ubiquitous in soft matter and biology, and chaotic active flows. In this Letter, we use continuum theory to examine phase separation of an active liquid crystal and a passive fluid and report two new results. First, we provide an analytical derivation of the activity-induced suppression of the phase boundary of the coexistence region - a result first reported in simulations and experiments. We show that the shift in the critical point is a result of the balance between self-stirring active flows and phase-separating diffusive fluxes. Second, we show that this same balance is responsible for dramatically changing the morphology of the phase separated state, resulting in the emergence of a new mixed active phase consisting of a dynamical filamentous active network that invades the entire system area, trapping droplets of passive material. This structure exists even for very low volume fractions of active material. Our work provides an important step towards the goal of understanding how to use activity as a new handle for sculpting interfaces.

cond-mat.soft↗

arXiv2024

cuPSS: a package for pseudo-spectral integration of stochastic PDEs

A large part of modern research, especially in the broad field of complex systems, relies on the numerical integration of PDEs, with and without stochastic noise. This is usually done with eiher in-house made codes or external packages like MATLAB, Mathematica, Fenicsx, OpenFOAM, Dedalus, and others. These packages rarely offer a good combination of speed, generality, and the option to easily add stochasticity to the system, while in-house codes depend on certain expertise to obtain good performance, and are usually written for each specific use case, sacrificing modularity and reusability. This paper introduces a package written in CUDA C++, thus enabling by default gpu acceleration, that performs pseudo-spectral integration of generic stochastic PDEs in flat lattices in one, two and three dimensions. This manuscript describes the basic functionality of cuPSS, with an example and benchmarking, showing that cuPSS offers a considerable improvement in speed over other popular finite-difference and spectral solvers.

physics.comp-ph↗

arXiv2024

Traveling waves at the surface of active liquid crystals

Active liquid crystals exert nonequilibrium stresses on their surroundings through constant consumption of energy, giving rise to dynamical steady states not present in equilibrium. The paradigmatic example of an active liquid crystal is a suspension of microtubule bundles powered by kinesin motor proteins, which exhibits self-sustained spatiotemporal chaotic flows. This system has been modelled using continuum theories that couple the microtubule orientation to active flows. Recently the focus has shifted to the interfacial properties of mixtures of active liquid crystals and passive fluids. Active/passive interfaces have been shown to support propagating capillary waves in the absence of inertia and offer a promising route for relating experimental parameters to those of the continuum theory. In this paper we report the derivation of a minimal model that captures the linear dynamics of the interface between an active liquid crystal and a passive fluid. We show that the dynamics of the interface, although powered by active flows throughout the bulk, is qualitatively captured by equations that couple non-reciprocally interface height and nematic director at the interface. This minimal model reproduces the dynamical structure factor evaluated from numerical simulations and the qualitative form of the wave dispersion relation seen in experiments.

cond-mat.soft↗

arXiv2024

Asymmetric fluctuations and self-folding of active interfaces

We study the structure and dynamics of the interface separating a passive fluid from a microtubule-based active fluid. Turbulent-like active flows power giant interfacial fluctuations, which exhibit pronounced asymmetry between regions of positive and negative curvature. Experiments, numerical simulations, and theoretical arguments reveal how the interface breaks up the spatial symmetry of the fundamental bend instability to generate local vortical flows that lead to asymmetric interface fluctuations. The magnitude of interface deformations increases with activity: In the high activity limit, the interface self-folds invaginating passive droplets and generating a foam-like phase, where active fluid is perforated with passive droplets. These results demonstrate how active stresses control the structure, dynamics, and break-up of soft, deformable, and reconfigurable liquid-liquid interfaces.

cond-mat.soft↗

arXiv2024

Adaptive Social Force Window Planner with Reinforcement Learning

Human-aware navigation is a complex task for mobile robots, requiring an autonomous navigation system capable of achieving efficient path planning together with socially compliant behaviors. Social planners usually add costs or constraints to the objective function, leading to intricate tuning processes or tailoring the solution to the specific social scenario. Machine Learning can enhance planners' versatility and help them learn complex social behaviors from data. This work proposes an adaptive social planner, using a Deep Reinforcement Learning agent to dynamically adjust the weighting parameters of the cost function used to evaluate trajectories. The resulting planner combines the robustness of the classic Dynamic Window Approach, integrated with a social cost based on the Social Force Model, and the flexibility of learning methods to boost the overall performance on social navigation tasks. Our extensive experimentation on different environments demonstrates the general advantage of the proposed method over static cost planners.

cs.RO↗

arXiv2023

Vorticity phase separation and defect lattices in the isotropic phase of active liquid crystals

We use numerical simulations and linear stability analysis to study the dynamics of an active liquid crystal film on a substrate in the regime where the passive system would be isotropic. Extensile activity builds up local orientational order and destabilizes the quiescent isotropic state above a critical activity value, eventually resulting in spatiotemporal chaotic dynamics akin to the one observed ubiquitously in the nematic state. Here we show that tuning substrate friction yields a variety of emergent structures at intermediate activity, including lattices of flow vortices with associated regular arrangements of topological defects and a new state where flow vortices trap pairs of $+1/2$ defect that chase each other tail. These chiral units spontaneously pick the sense of rotation and organize in a hexagonal lattice, surrounded by a diffuse flow of opposite rotation to maintain zero net vorticity. The length scale of these emergent structures is set by the screening length $l_η=\sqrt{η/Γ}$ of the flow, controlled by the shear viscosity $η$ and the substrate friction $Γ$, and can be captured by simple mode selection of the vortical flows. We demonstrate that the emergence of coherent structures can be interpreted as a phase separation of vorticity, where friction plays a role akin to that of birth/death processes in breaking conservation of the phase separating species and selecting a characteristic scale for the patterns. Our work shows that friction provides an experimentally accessible tuning parameter for designing controlled active flows.

cond-mat.soft↗

arXiv2023

HuNavSim: A ROS 2 Human Navigation Simulator for Benchmarking Human-Aware Robot Navigation

This work presents the Human Navigation Simulator (HuNavSim), a novel open-source tool for the simulation of different human-agent navigation behaviors in scenarios with mobile robots. The tool, the first programmed under the ROS 2 framework, can be employed along with different well-known robotics simulators like Gazebo. The main goal is to ease the development and evaluation of human-aware robot navigation systems in simulation. Besides a general human-navigation model, HuNavSim includes, as a novelty, a rich set of individual and realistic human navigation behaviors and a complete set of metrics for social navigation benchmarking.

cs.RO↗

arXiv2022

Activity-suppressed phase separation

We use a continuum model to examine the effect of activity on a phase separating mixture of an extensile active nematic and a passive fluid. We highlight the distinct role of previously considered interfacial active stresses and bulk active stresses that couple to liquid crystalline degrees of freedom. Interfacial active stresses can arrest phase separation, as previously demonstrated. Bulk extensile active stresses can additionally strongly suppress phase separation by sustained self-stirring of the fluid, substantially reducing the size of the coexistence region in the temperature/concentration plane relative to that of the passive system. The phase separated state is a dynamical emulsion-like steady state of continuously splitting and merging droplets, as suggested by recent experiments. Using scaling analysis and simulations, we identify various regimes for the dependence of droplet size on activity. These results can provide a criterion for identifying the mechanisms responsible for arresting phase separation in experiments.

cond-mat.soft↗

arXiv2022

OG-SGG: Ontology-Guided Scene Graph Generation. A Case Study in Transfer Learning for Telepresence Robotics

Scene graph generation from images is a task of great interest to applications such as robotics, because graphs are the main way to represent knowledge about the world and regulate human-robot interactions in tasks such as Visual Question Answering (VQA). Unfortunately, its corresponding area of machine learning is still relatively in its infancy, and the solutions currently offered do not specialize well in concrete usage scenarios. Specifically, they do not take existing "expert" knowledge about the domain world into account; and that might indeed be necessary in order to provide the level of reliability demanded by the use case scenarios. In this paper, we propose an initial approximation to a framework called Ontology-Guided Scene Graph Generation (OG-SGG), that can improve the performance of an existing machine learning based scene graph generator using prior knowledge supplied in the form of an ontology (specifically, using the axioms defined within); and we present results evaluated on a specific scenario founded in telepresence robotics. These results show quantitative and qualitative improvements in the generated scene graphs.

cs.RO↗

arXiv2022

Controlling liquid-liquid phase behavior with an active fluid

Demixing of binary liquids is a ubiquitous transition, which is explained using a well-established thermodynamic formalism that requires equality of intensive thermodynamics parameters across the phase boundaries. Demixing transitions also occur when binary fluid mixtures are driven away from equilibrium, for example, by external shear flow. Predicting demixing transition under non-equilibrium non-potential conditions remains, however, a challenge. We drive liquid-liquid phase separation (LLPS) of attractive DNA nanostar molecules away from equilibrium using an internally driven microtubule-based active fluid. Activity lowers the critical temperature and narrows the coexistence concentrations, but only when there are mechanical bonds between the liquid droplets and the reconfiguring active fluid. Similar behaviors are observed in numerical simulations, suggesting that activity suppression of liquid-liquid phase separation is a generic feature of active LLPS. Our work describes a platform for building soft active materials with feedback control while also providing insight into cell biology, where phase separation emerged as a ubiquitous self-organizational principle.

cond-mat.soft↗

arXiv2021

Autonomous Aerial Robot for High-Speed Search and Intercept Applications

In recent years, high-speed navigation and environment interaction in the context of aerial robotics has become a field of interest for several academic and industrial research studies. In particular, Search and Intercept (SaI) applications for aerial robots pose a compelling research area due to their potential usability in several environments. Nevertheless, SaI tasks involve a challenging development regarding sensory weight, on-board computation resources, actuation design and algorithms for perception and control, among others. In this work, a fully-autonomous aerial robot for high-speed object grasping has been proposed. As an additional sub-task, our system is able to autonomously pierce balloons located in poles close to the surface. Our first contribution is the design of the aerial robot at an actuation and sensory level consisting of a novel gripper design with additional sensors enabling the robot to grasp objects at high speeds. The second contribution is a complete software framework consisting of perception, state estimation, motion planning, motion control and mission control in order to rapid- and robustly perform the autonomous grasping mission. Our approach has been validated in a challenging international competition and has shown outstanding results, being able to autonomously search, follow and grasp a moving object at 6 m/s in an outdoor environment

cs.RO↗

arXiv2021

DLL: Direct LIDAR Localization. A map-based localization approach for aerial robots

This paper presents DLL, a fast direct map-based localization technique using 3D LIDAR for its application to aerial robots. DLL implements a point cloud to map registration based on non-linear optimization of the distance of the points and the map, thus not requiring features, neither point correspondences. Given an initial pose, the method is able to track the pose of the robot by refining the predicted pose from odometry. Through benchmarks using real datasets and simulations, we show how the method performs much better than Monte-Carlo localization methods and achieves comparable precision to other optimization-based approaches but running one order of magnitude faster. The method is also robust under odometric errors. The approach has been implemented under the Robot Operating System (ROS), and it is publicly available.

cs.RO↗

arXiv2021

Skyeye Team at MBZIRC 2020: A team of aerial and ground robots for GPS-denied autonomous fire extinguishing in an urban building scenario

The paper presents a framework for fire extinguishing in an urban scenario by a team of aerial and ground robots. The system was developed to address Challenge 3 of the 2020Mohamed Bin Zayed International Robotics Challenge (MBZIRC). The challenge required to autonomously detect, locate and extinguish fires on different floors of a building, as well as in its surroundings. The multi-robot system developed consists of a heterogeneous robot team of up to three Unmanned Aerial Vehicles (UAV) and one Unmanned Ground Vehicle (UGV). We describe the main hardware and software components for UAV and UGVplatforms and also present the main algorithmic components of the system: a 3D LIDAR-based mapping and localization module able to work in GPS-denied scenarios; a global planner and a fast local re-planning system for robot navigation; infrared-based perception and robot actuation control for fire extinguishing; and a mission executive and coordination module based on Behavior Trees. The paper finally describes the results obtained during the competition, where the system worked fully autonomously and scored in all the trials performed. The presented system ended in 7th position out of 20 teams in the Challenge3 competition and in 5th position (out of 17 teams) in the Challenge 3 entry to the Grand Finale (Grand Challenge) of MBZIRC 2020 competition.

cs.RO↗

arXiv2020

Stealth entropy production in active field theories near Ising critical points

We address the steady-state entropy production rate (EPR) of active scalar $ϕ^4$ theories, which lack time-reversal symmetry, close to a phase-separation critical point. We consider both nonconserved (Model A) and conserved (Model B) dynamics at Gaussian level, and also address the former at leading order in $ε= 4-d$. In each case, activity is irrelevant in the RG sense: the active model lies in the same (dynamic Ising) universality class as its time-reversible counterpart. Hence one might expect that activity brings no new critical behavior. Here we show instead that the EPR per spacetime correlation volume either remains finite or diverges on approach to criticality. A nontrivial critical scaling for entropy production thus ranks among universal dynamic Ising-class properties.

cond-mat.stat-mech↗

arXiv2020

Inference, prediction and optimization of non-pharmaceutical interventions using compartment models: the PyRoss library

PyRoss is an open-source Python library that offers an integrated platform for inference, prediction and optimisation of NPIs in age- and contact-structured epidemiological compartment models. This report outlines the rationale and functionality of the PyRoss library, with various illustrations and examples focusing on well-mixed, age-structured populations. The PyRoss library supports arbitrary structured models formulated stochastically (as master equations) or deterministically (as ODEs) and allows mid-run transitioning from one to the other. By supporting additional compartmental subdivision ad libitum, PyRoss can emulate time-since-infection models and allows medical stages such as hospitalization or quarantine to be modelled and forecast. The PyRoss library enables fitting to epidemiological data, as available, using Bayesian parameter inference, so that competing models can be weighed by their evidence. PyRoss allows fully Bayesian forecasts of the impact of idealized NPIs by convolving uncertainties arising from epidemiological data, model choice, parameters, and intrinsic stochasticity. Algorithms to optimize time-dependent NPI scenarios against user-defined cost functions are included. PyRoss's current age-structured compartment framework for well-mixed populations will in future reports be extended to include compartments structured by location, occupation, use of travel networks and other attributes relevant to assessing disease spread and the impact of NPIs. We argue that such compartment models, by allowing social data of arbitrary granularity to be combined with Bayesian parameter estimation for poorly-known disease variables, could enable more powerful and robust prediction than other approaches to detailed epidemic modelling. We invite others to use the PyRoss library for research to address today's COVID-19 crisis, and to plan for future pandemics.

q-bio.PE↗

arXiv2018

From bulk to microphase separation in scalar active matter: A perturbative renormalization group analysis

We consider a dynamical field theory (Active Model B+) that minimally extends the equilibrium Model B for diffusive phase separation of a scalar field, by adding leading-order terms that break time-reversal symmetry. It was recently shown that such active terms can cause the bulk phase separation of Model B to be replaced by a steady state of microphase separation at a finite length scale. This phenomenon was understood at mean-field level as due to the activity-induced reversal of the Ostwald ripening mechanism, which provides the kinetic pathway to bulk phase separation in passive fluids. This reversal occurs only in certain ranges for the activity parameters. In this paper we go beyond such a mean-field analysis and develop a $1$-loop Renormalisation Group (RG) approach. We first show that, in the parameter range where bulk phase separation is still present, the critical point belongs formally to the same (Wilson-Fisher) universality class as the passive Model B. In contrast, in a parameter range associated with microphase separation, we find that an unstable non-equilibrium fixed point of the RG flow arises for $d\geq 2$, colliding with the Wilson-Fisher point in $d\to 2^+$ and making it unstable in $d=2$. At large activity, the flow in this region is towards strong coupling. We argue that the phase transition to microphase separation in active systems, in the physically relevant dimensions $d=2$ and $3$, very probably belongs to a new non-equilibrium universality class. Because it is governed by the strong-coupling regime of the RG flow, our perturbative analysis leaves open the quantitative characterization of this new class.

cond-mat.stat-mech↗