Continuous Management of Modes and Resources in Detection of a Moving Target

This paper deals with optimization of divisible resources aimed to the detection of a moving target following a Markovian movement or a conditionally deterministic motion. Our work extends Brown's spatial optimization method. By use of a generalized linear formalism, we develop a method for optimizing the search efforts both spatially and temporally (modeling resource renew), with management of multiple resource types or multi-modes resources. Such optimization involves also the fusion of several detection devices, in order to make them work together efficiently

Intrinsic determinants of mango tree growth and reproduction: Consequences on functional-structural modeling

International audienceno abstrac

A Column Generation Based Label Correcting Approach for the Sensor Management in an Information Collection Process

International audienceThis paper deals with problems of sensor management in a human driven information collection process. This applicative context results in complex sensor-to-task assignment problems, which encompass several difficulties. First of all, the tasks take the form of several information requirements, which are linked together by logical connections and priority rankings. Second, the assignment problem is correlated by many constraint paradigms. Our problem is a variant of Vehicle Routing Problem with Time Windows (VRPTW), and it also implements resource constraints including refuelling issues. For solving this problem, we propose a column generation approach, where the label correcting method is used to treat the sub-problem. The efficiency of our approach is evaluated by comparing with solution given by CPLEX on different scenarios

Minimax Optimization of Continuous Search Efforts for the Detection of a Target

Analytical resolution of search theory problems, as formalized by B.O. Koopman, may be applied with some model extension to various resource management and data fusion issues. Such method is based on a probabilistic prior about the target. Even so, this approximation forbids any reactive behavior of the target. As a preliminary step towards reactive target study stands the problem of resource placement under a minimax game context. This report is related to Nakai's work about the game placement of resources for the detection of a stationary target. However, this initial problem is extended by adding new and more general constraints, allowing a more subtle modeling of the target and resource behaviors

Une méthode de génération de colonnes pour la planification des capteurs dans un processus de collecte d'informations

National audienceDans ce papier, nous considérerons le problème de la planification de capteurs sous le contrôle d'équipes humaines. Le processus de planification est divisé en deux étapes : la première donne lieu à une définition du problème d'affectation par une déclinaison de demandes informelles en requêtes formalisées et conditionnées par des contraintes logiques, des contraintes de trajectoire des moyens d'acquisition et des contraintes temporelles ; la seconde correspond à la réalisation effective du processus d'optimisation. Dans ce type de planification, l'interaction humaine avec le processus d'optimisation est fondamentale

Deciphering mango tree asynchronisms using Markov tree and probabilistic graphical models

ISBN 978-951-651-408-9International audienceTree development is often characterised by complex dependencies between daughter growth units (GUs) deriving from a given mother GU, the so-called sister GUs. These dependencies directly affect the reproductive and vegetative phenological patterns that are at the origin of asynchronisms between adjacent GUs, eventually leading to within-canopy patchiness. These phenomena are rather common on tropical fruit-trees. We introduce new parsimonious statistical models to identify such dependencies. The proposed approach is illustrated on mango tree, a tropical species with a particularly complex timing of development. We focus especially on differences on fates and dates of burst between the daughter GUs issued from a same mother GU

A Column Generation Approach for Coordination and Control of Multiple UAVs

International audienceIn this work, we consider the problem of autonomous task allocation and trajectory planning for a set of UAVs. This is a bi-level problem: the upper-level is a task assignment problem, subjected to UAV capability constraints; the lower-level constructs the detailed trajectory of UAVs, subjected to dynamics, avoidance and dependency constraints. Although the entire problem can be formulated as a mixed-integer linear program (MILP), and thus it can be solved by available software, the computational time increases intensively. For solving more efficiently this problem we propose a new approach based on the column generation method. Then, the two branching techniques will be investigated in order to obtain a branch-and-price scheme for this problem. The efficiency of our approach is evaluated by comparing with solution given by CPLEX on different scenarios

Planning Sensors with Cost-Restricted Subprocess Calls: A Rare-Event Simulation Approach

International audienceThis paper deals with optimal sensor planning in the contextof an observation mission. In order to accomplish this mission, theobserver may request some intelligence teams for preliminary prior information.Since team requests are expensive and resources are bound,the entire process results in a two-level optimization, the first level beingan experiment devoted to enhance the criterion modelling. The paperproposes a solve of this problem by rare-event simulation, and a missionscenario is addressed

Map-reduce implementation of belief combination rules

International audienceThis paper presents a generic and versatile approach for implementing combining rules on preprocessed belieffunctions, issuing from a large population of information sources. In this paper, we address two issues, whichare the intrinsic complexity of the rules processing, and the possible large amount of requested combinations.We present a fully distributed approach, based on a map-reduce (Spark) implementation