Abstract: In tracking algorithms where measurements from various sensors are combined the track state representation is usually dependent on the type of sensor information that is received. When a multi-hypothesis tracking algorithm is used the probabilities
of the different hypotheses containing tracks in different representations need to be re-evaluated when track state representations are changed. For the particular case of trilateration a method is presented to adapt the state representation as more information becomes available. A method is presented to re-evaluate the probabilities of the
hypotheses leading to a method for the trilateration case. This is illustrated by a simple example.
Abstract: This paper presents a sampling strategy for
mobile gas sensors. Sampling points are selected using a modified artificial potential field (APF) approach, which balances multiple criteria to direct sensor measurements towards locations of high mean concentration, high concentration variance and areas for which the uncertainty about the gas distribution model is still large. By selecting in each step the most often suggested close-by easurement
location, the proposed approach introduces a locality constraint that allows planning suitable paths for mobile gas sensors. Initial results in simulation and in real-world experiments with a gas-sensitive micro-drone demonstrate the suitability of the proposed sampling strategy for gas distribution mapping and its use for gas source localization.
Abstract: One of the major ICIS valorization efforts in 2006 concerned the dissemination of ICIS’ results to the Gemeente Borsele (in the Province of Zeeland, The Netherlands). DECIS Lab and Gemeente Borsele have jointly conducted empirical research in the context of a crisis management exercise for Gemeente Borsele. DECIS Lab was involved to set up the crisis management exercise experiment and according measurements regarding an improvement in internal communication at Gemeente Borsele. The major objectives of DECIS Lab (collect crisis data, acquire domain knowledge, discover feasibility) and Gemeente Borsele (improve internal communication, and involve entire internal crisis management organization) were mostly achieved. This report contains our evaluation as a whole together with specific results, as presented to Gemeente Borsele.
Abstract: This research report describes an experiment regarding assessing the effectiveness of actor-agent teams within the SEAT project in the CDM cluster in the ICIS research program. This document focuses on the background of actor-agent teaming, and on a methodology to assess the performance of an actor-agent team in comparison with an actor-only team. The experimental design is described together with the measurements and analysis. The results show that the experimental setup using the REsearch and Simulation toolKit(RESK) provides a repeatable construct. The results of the current performance comparison show no large decrement; but also not a large increment in performance. This is mostly due to the current (low) level ofagent complexity, where improvements are needed in communication capabilities and (more) team-oriented helpful behavior.
Abstract: This white paper contains the report of a first try-out experiment regarding assessing the effectiveness of actor-agent teams within the SEAT project. This document describes the background, experimental design and measurements and analysis of a pilot experiment conducted in July 2008 with an actor-only team.
Abstract: Gas distribution models can provide comprehensive information about a large
number of gas concentration measurements, highlighting, for example, areas of unusual
gas accumulation. They can also help to locate gas sources and to plan where
future measurements should be carried out. Current physical modeling methods,
however, are computationally expensive and not applicable for real world scenarios
with real-time and high resolution demands. This chapter reviews kernel methods
that statistically model gas distribution. Gas measurements are treated as random
variables, and the gas distribution is predicted at unseen locations either using a
kernel density estimation or a kernel regression approach. The resulting statistical apmodels
do not make strong assumptions about the functional form of the gas distribution,
such as the number or locations of gas sources, for example. The major
focus of this chapter is on two-dimensional models that provide estimates for the
means and predictive variances of the distribution. Furthermore, three extensions
to the presented kernel density estimation algorithm are described, which allow to
include wind information, to extend the model to three dimensions, and to reflect
time-dependent changes of the random process that generates the gas distribution
measurements. All methods are discussed based on experimental validation using
real sensor data.
Abstract: To study gas dispersion, several statistical gas distribution modelling approaches have
been proposed recently. A crucial assumption in these approaches is that gas distribution models are
learned from measurements that are generated by a time-invariant random process which can capture
certain fluctuations in the gas distribution. More accurate models can be obtained by modelling
changes in the random process over time. In this work we propose a time-scale parameter that relates
the age of measurements to their validity to build the gas distribution model in a recency function.
The parameters of the recency function define a time-scale and can be learned. The time-scale
represents a compromise between two conflicting requirements to obtain accurate gas distribution
models: using as many measurements as possible and using only very recent measurements. We
have studied several recency functions in a time-dependent extension of the Kernel DM+V. Based
on real-world experiments and simulations of gas dispersal (presented in this paper) we demonstrate
that TD Kernel DM+V improves the obtained gas distribution models in dynamic situations. This
represents an important step towards statistical modelling of evolving gas distributions.
Abstract: Conducting empirical research involves a balancing act between scientific rigor and real-life pragmatics. The Delft Co-operation on Intelligent Systems (D-CIS) laboratory researches systems-of-systems consisting of the human and artificial systems involved in collaborative decision-making under chaotic circumstances. An important objective is the usefulness of our results in our major application domain: crisis management. The D-CIS lab was involved in setting up a crisis management exercise experiment and the according measurements regarding an improvement in internal communication at Gemeente (Municipality) Borsele. In this paper, the empirical research regarding this experiment, the methodology and its results are briefly outlined. The main lessons learned concern the interrelationship between the scenario, experiment and measurements, the problem of acquiring usable data and the challenges of conducting grounded research.
Abstract: Conducting empirical research involves a balancing act between scientific rigor and real-life pragmatics. DECIS Lab researches systems-of-systems, consisting of humans and artificial systems involved in collaborative decision making under chaotic circumstances. An important objective is the usefulness of our results to our major application domain: crisis management. DECIS Lab was involved to set up a crisis management exercise experiment and according measurements regarding an improvement in internal communication at Gemeente (Municipality) Borsele. In this paper the empirical research regarding this experiment, the methodology and its results are briefly outlined. Our main lessons learned concern the interrelationship between scenario, experiment and measurements; the problem of acquiring usable data; and the challenges of conducting grounded research.
Abstract: This deliverable is a demonstrator of the preliminary UAV (Unmanned Aerial Vehicle) system software packaged for the control and simulation of mini UAVs. The software package allows actual operation of mini UAVs (under development), hardware in the loop simulation and full simulation.
The demonstrator simulates the flight of four UAVs of the EasyStar type above a virtual compound near Kandahar, Afghanistan. The mission over Afghanistan was inspired by participating in the Frame Game 2006. The software supports missions with true WGS84 (GPS) coordinates around the world when the appropriate maps are provided. At this time the Kandahar map is fully supported but maps of Delft and Braunschweig (Germany) have also been loaded in earlier versions.
This version allows the simulation of the Aero-DPN UAV-Flight. In this scenario the UAV is located at a sports field upwind from the stadium in Lima city (Brussels) where an explosion has taken place. A flightplan can be loaded to guide the UAV along a number of waypoints where radiation measurements will be taken and sent to the DPN software (not part of this bundle, by Gregor Pavlin). This scenario serves to demonstrate how the UAV can be deployed in a crisis scenario and be combined with other ICIS projects software (DPN). In addition to the first release this version better supports the human operator to control the UAV in a flexible manner.