Sublinear algorithms for local graph centrality estimation

We study the complexity of local graph centrality estimation, with the goal of approximating the centrality score of a given target node while exploring only a sublinear number of nodes/arcs of the graph and performing a sublinear number of elementary operations. We develop a technique, that we apply to the PageRank and Heat Kernel centralities, for building a low-variance score estimator through a local exploration of the graph. We obtain an algorithm that, given any node in any graph of $m$ arcs, with probability $(1-\delta)$ computes a multiplicative $(1\pm\epsilon)$-approximation of its score by examining only $\tilde{O}(\min(m^{2/3} \Delta^{1/3} d^{-2/3},\, m^{4/5} d^{-3/5}))$ nodes/arcs, where $\Delta$ and $d$ are respectively the maximum and average outdegree of the graph (omitting for readability $\operatorname{poly}(\epsilon^{-1})$ and $\operatorname{polylog}(\delta^{-1})$ factors). A similar bound holds for computational complexity. We also prove a lower bound of $\Omega(\min(m^{1/2} \Delta^{1/2} d^{-1/2}, \, m^{2/3} d^{-1/3}))$ for both query complexity and computational complexity. Moreover, our technique yields a $\tilde{O}(n^{2/3})$ query complexity algorithm for the graph access model of [Brautbar et al., 2010], widely used in social network mining; we show this algorithm is optimal up to a sublogarithmic factor. These are the first algorithms yielding worst-case sublinear bounds for general directed graphs and any choice of the target node.Comment: 29 pages, 1 figur

An Effective Multi-Cue Positioning System for Agricultural Robotics

The self-localization capability is a crucial component for Unmanned Ground Vehicles (UGV) in farming applications. Approaches based solely on visual cues or on low-cost GPS are easily prone to fail in such scenarios. In this paper, we present a robust and accurate 3D global pose estimation framework, designed to take full advantage of heterogeneous sensory data. By modeling the pose estimation problem as a pose graph optimization, our approach simultaneously mitigates the cumulative drift introduced by motion estimation systems (wheel odometry, visual odometry, ...), and the noise introduced by raw GPS readings. Along with a suitable motion model, our system also integrates two additional types of constraints: (i) a Digital Elevation Model and (ii) a Markov Random Field assumption. We demonstrate how using these additional cues substantially reduces the error along the altitude axis and, moreover, how this benefit spreads to the other components of the state. We report exhaustive experiments combining several sensor setups, showing accuracy improvements ranging from 37% to 76% with respect to the exclusive use of a GPS sensor. We show that our approach provides accurate results even if the GPS unexpectedly changes positioning mode. The code of our system along with the acquired datasets are released with this paper.Comment: Accepted for publication in IEEE Robotics and Automation Letters, 201

On Approximating the Stationary Distribution of Time-reversible Markov Chains

Approximating the stationary probability of a state in a Markov chain through Markov chain Monte Carlo techniques is, in general, inefficient. Standard random walk approaches require tilde{O}(tau/pi(v)) operations to approximate the probability pi(v) of a state v in a chain with mixing time tau, and even the best available techniques still have complexity tilde{O}(tau^1.5 / pi(v)^0.5); and since these complexities depend inversely on pi(v), they can grow beyond any bound in the size of the chain or in its mixing time. In this paper we show that, for time-reversible Markov chains, there exists a simple randomized approximation algorithm that breaks this "small-pi(v) barrier"

Numerical Modelling of Droplets and Beads Behavior over Super-Hydrophobic and Hydrophilic Coatings under in-Flight Icing Conditions

Featured Application: Use of hydrophobic coatings as passive inflight icing safety device. Current technology has produced a wide range of advanced micro-structured surfaces, designed for achieving the best wettability and adhesion performances for each specific application. In the context of in-flight icing simulations, this opens new challenges since the current most popular and successful ice accretion prediction tools neglect the details of the droplet behavior opting for a continuous film model. Here, a phenomenological model, following, in a Lagrangian approach, the evolution of the single droplets from the impinging to the onset of rivulets, is developed to simulate the performances of super-hydrophobic surfaces in icing application. Possible rebound and droplet spread on the impact, coalescence, single ice bead formation and droplet to rivulet transition are taken into account. The first validation shows how the models are able to predict the anti-icing capability of a super-hydrophobic surface coupled with a heating system

Design of a hydraulic servo-actuation fed by a regenerative braking system

Many conventional truck and working machines are equipped with additional hydraulic tooling or manipulation systems which are usually fed through a mechanical connection with the internal combustion engine, involving a poor efficiency. In particular, this is a common situation for industrial vehicles whose mission profiles involves a relevant consumption of energy by the on board hydraulic systems, respect to the one really needed for only traction purpose. In this work it is proposed an innovative solution based on the adoption of a system aimed to recover braking energy in order to feed an efficient on board hydraulic actuation system. The proposed system is then adopted to a real application, an Isuzu truck equipped with a hydraulic tooling for garbage collection. A prototype of the system has been designed, assembled and tested showing a relevant improvement of system efficiency and the feasibility of the proposed approach. In the paper the proposed solution is presented, showing the simulation models and preliminary validation results including experimental devices assembled to perform the tests