Distributed Estimation with Information-Seeking Control in Agent Network

We introduce a distributed, cooperative framework and method for Bayesian estimation and control in decentralized agent networks. Our framework combines joint estimation of time-varying global and local states with information-seeking control optimizing the behavior of the agents. It is suited to nonlinear and non-Gaussian problems and, in particular, to location-aware networks. For cooperative estimation, a combination of belief propagation message passing and consensus is used. For cooperative control, the negative posterior joint entropy of all states is maximized via a gradient ascent. The estimation layer provides the control layer with probabilistic information in the form of sample representations of probability distributions. Simulation results demonstrate intelligent behavior of the agents and excellent estimation performance for a simultaneous self-localization and target tracking problem. In a cooperative localization scenario with only one anchor, mobile agents can localize themselves after a short time with an accuracy that is higher than the accuracy of the performed distance measurements.Comment: 17 pages, 10 figure

Multisensor Poisson Multi-Bernoulli Filter for Joint Target-Sensor State Tracking

In a typical multitarget tracking (MTT) scenario, the sensor state is either assumed known, or tracking is performed in the sensor's (relative) coordinate frame. This assumption does not hold when the sensor, e.g., an automotive radar, is mounted on a vehicle, and the target state should be represented in a global (absolute) coordinate frame. Then it is important to consider the uncertain location of the vehicle on which the sensor is mounted for MTT. In this paper, we present a multisensor low complexity Poisson multi-Bernoulli MTT filter, which jointly tracks the uncertain vehicle state and target states. Measurements collected by different sensors mounted on multiple vehicles with varying location uncertainty are incorporated sequentially based on the arrival of new sensor measurements. In doing so, targets observed from a sensor mounted on a well-localized vehicle reduce the state uncertainty of other poorly localized vehicles, provided that a common non-empty subset of targets is observed. A low complexity filter is obtained by approximations of the joint sensor-feature state density minimizing the Kullback-Leibler divergence (KLD). Results from synthetic as well as experimental measurement data, collected in a vehicle driving scenario, demonstrate the performance benefits of joint vehicle-target state tracking.Comment: 13 pages, 7 figure

Modelling of river dike breach type physical test flow with Telemac-2D

Water Qualit

An Integrated Approach To Simulate Flooding Due To River Dike Breach

This paper presents an integrated approach that enables the simultaneous modeling of dike breaching process and flood propagation. The dike breaching process is modelled with a simple breach model implemented into a 2-dimensional hydrodynamic flood model – Telemac2D. Telemac2D models the propagation of the arising flood into the hinterland. The breach model generalizes dike breaching process in two general stages. In the first stage, dike breaching is predominantly vertical with limited lateral breach growth; and in the second stage breach grows only laterally. The breach model requires breach location, breach duration, and length and axis of dike affected by the breach as input parameters. Breach starts at the center of the dike length affected by the breach and can be initiated in three different ways: at a given time, based on water level on the dike or based on water level at a given point. The first stage takes one tenth of the total time required for the entire breach and has a breach width equal to one tenth of the final breach width. The approach is exemplarily applied to model the year 1996 Awash River dike breach flood at Wonji, Ethiopia, a historic dike breach flood that destroyed the sugar plantation and offices of Wonji Shoa Sugar Factory. The water depth calculated with the numerical model is in good agreement with the water level mark left on buildings as witnessed by people present at the place after the disaster, including the dike foreman

Mapping of Multiple Linked Green Infrastructure Systems in Rainfall-runoff Models

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive