Stefania Monica

UWB-based localization in large indoor scenarios: optimized placement of anchor nodes

In this paper, we consider the problem of locating a target node (TN) moving along a corridor in a large industrial environment by means of ultrawide band signaling from fixed anchor nodes (ANs) uniformly positioned at the same height on both sides of the corridor. For a representative geometry of a large indoor (industrial) scenario, we formulate an analytical approach to the optimized placement (in terms of internode distance) of ANs using the criterion of minimizing the average mean square error (MSE) in the time-difference-of-arrival-based estimated positions of the TN. Under the assumption of a fixed variance of the range estimation error, we derive a simple closed-form expression for the optimal inter-AN distance in terms of the corridor width and the height of the ANs. The effectiveness of the analytical approach is confirmed by simulations. We also show that the proposed approach allows the MSE in the TN position estimates to reach the Cramer Rao lower bound.

An experimental model for UWB distance measurements and its application to localization problems

The goal of this paper is to analyze the impact of an accurate statistical model for distance estimation on the localization accuracy of practical Ultra Wide Band (UWB) systems. Our experimental investigation is based on the use of a particular type of UWB sensors, namely the PulsON 410 Ranging and Communications Modules (P410 RCMs) produced by Time Domain. First, we derive a statistical model for distance estimate between pairs of UWB sensors, finding a (linear) relation between the inter-modules distance and the average distance error. Similarly, a (linear) approximation for the standard deviation of the distance error is derived. Finally, we consider four P410 RCMs: assuming to know the positions of three of them, the position of the remaining one is estimated relying on distance measurements between pairs of them. Our results show that the localization accuracy is improved taking into account the statistical model for the distance estimate derived in the first part of the paper.

Accurate Indoor Localization with UWB Wireless Sensor Networks

Wireless Sensor Networks (WSNs) consist of a collection of spatially distributed radio transceivers with attached sensors that can measure and gather information from the environment. In this paper, we focus on the application of WSNs to indoor localization and, for this purpose, we propose the use of a Ultra Wide Band (UWB) WSN. The use of UWB signals guarantees robust performance in dense multipath environments, making them an attractive choice for indoor localization. In this paper, we discuss on different localization strategies: first classic geometric approaches are considered, then the mathematical framework is re-interpreted as an optimization problem. In the latter context, we propose the use of Particle Swarm Optimization (PSO) in particular, which can overcome limitations of classic (geometric) approaches.

Particle Swarm Optimization for Auto-localization of Nodes in Wireless Sensor Networks

In this paper, we consider the problem of auto-localization of the nodes of a static Wireless Sensor Network (WSN) where nodes communicate through Ultra Wide Band (UWB) signaling. In particular, we investigate auto-localization of the nodes assuming to know the position of a few initial nodes, denoted as “beacons”. In the considered scenario, we compare the location accuracy obtained with the widely used Two-Stage Maximum-Likelihood algorithm with that achieved with an algorithm based on Particle Swarming Optimization (PSO). Accurate simulation results show that the latter can significantly outperform the former.

A swarm-based approach to real-time 3D indoor localization

Graphical abstractDisplay Omitted In this paper, the problem of indoor localization in wireless networks is addressed relying on a swarm-based approach. We assume to know the positions of a few number of sensor nodes, denoted as anchor nodes (ANs), and we aim at finding the position of a target node (TN) on the basis of the estimated distances between each AN and the considered TN. Since ultra wide band (UWB) technology is particularly suited for localization purposes (owing to its remarkable time resolution), we consider a network composed of UWB devices. More precisely, we carry out an experimental investigation using the PulsOn 410 ranging and communication modules (RCMs) produced by time domain. Using four of them as ANs and one of them as TN, various topologies are considered in order to evaluate the accuracy of the proposed swarm-based localization approach, which relies on the pairwise (AN-TN) distances estimated by the RCMs. Then, we investigate how the accuracy of the proposed localization algorithm changes if we apply to the distance estimates a recently proposed stochastic correction, which is designed to reduce the distance estimation error. Our experimental results show that a good accuracy is obtained in all the considered scenarios, especially when applying the proposed swarm-based localization algorithm to the stochastically corrected distances. The obtained results are satisfying also in terms of software execution time, making the proposed approach applicable to real-time dynamic localization problems.

Optimized anchors placement: An analytical approach in UWB-based TDOA localization

In this paper, we consider the problem of locating an Automated Guided Vehicle (AGV) which moves on a plane in an industrial environment by means of Ultra-Wide Band (UWB) signaling from fixed Anchors Nodes (ANs) situated in the (three-dimensional) space. An analytical approach to optimize, under proper (realistic) constraints, the placement of the ANs used to locate the AGV is proposed. Analytical results are confirmed by simulations.

An analytic study of opinion dynamics in multi-agent systems

This paper presents an analytic approach that can be used to study opinion dynamics in multi-agent systems. The results of such an analytic approach can be used as a descriptive tool capable of predicting the long-term properties of a multi-agent system, and they can also be considered a prescriptive tool that supports the design of multi-agent systems with desired asymptotic characteristics. The agents that form the multi-agent system are divided into disjoint classes characterized by different values of fixed parameters to account for the specific behaviors of single agents. Each class is characterized by the number of agents in it, by the initial distribution of the opinion, and by the characteristic propensity of single agents to change their respective opinions when interacting with other agents. The proposed approach is based on the possibility of interpreting the dynamics of the opinion in terms of the kinetic theory of gas mixtures, which allows expressing the dynamics of the average opinion of each class in terms of a suitable differential problem that can be used to derive interesting asymptotic properties. Analytic solutions of the obtained differential problem are derived and it is shown that, under suitable hypotheses, the average opinions of all classes of agents converge to the same value. The results presented in this paper differ from those commonly derived in standard kinetic theory of gas mixtures because the microscopic equations which describe the effects of interactions among agents are explicitly meant to model opinion dynamics, and they are different from those normally used to describe collisions among molecules in a gas. All presented analytic results are confirmed by simulations presented at the end of the paper.

A Comparison of Accurate Indoor Localization of Static Targets via WiFi and UWB Ranging

This paper compares Ultra-Wide Band (UWB) and WiFi technologies as sources of information for accurate localization of static targets in indoor scenarios. Such technologies offer different localization accuracy and they are also characterized by different applicability. UWB provides very accurate localization information, but it requires a dedicated infrastructure and it is not yet widely available in mobile appliances. WiFi gives less accurate localization information but it is integrated in all modern mobile appliances and it does not require a dedicated infrastructure. This paper details on accuracy versus wide applicability trade-off and it provides quantitative criteria to choose one technology or the other. The discussed results are obtained using a new add-on module for JADE which allows embedding diverse sources of ranging information and localization algorithms.

Kinetic Description of Opinion Evolution in Multi-agent Systems: Analytic Model and Simulations

In this paper we consider multi-agent systems where interactions among agents are modeled using a kinetic approach. While kinetic theory aims at studying macroscopic properties of gases starting from microscopic interactions among molecules, we are interested in modeling the global behaviour of multi-agent systems on the basis of local interactions among pairs of agents. In particular, here we study the dynamics of opinion formation. Given a microscopic description of each single interaction, we derive stationary profiles for the global opinion. Analytic results are validated by simulations obtained by implementing the proposed theoretical model.

A Kinetic Study of Opinion Dynamics in Multi-agent Systems

In this paper we rephrase the problem of opinion formation from a physical viewpoint. We consider a multi-agent system where each agent is associated with an opinion and interacts with any other agent. Interpreting the agents as the molecules of a gas, we model the opinion evolution according to a kinetic model based on the analysis of interactions among agents. From a microscopic description of each interaction between pairs of agents, we derive the stationary profiles under given assumption. Results show that, depending on the average opinion and on the model parameters, different profiles can be found, with different properties. Each stationary profile is characterized by the presence of one or two maxima.