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Magali Barbier

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4 papers

2 author rows

IROS Conference 2022 Conference Paper

A Hierarchical Deliberative Architecture Framework based on Goal Decomposition

Charles Lesire
Rafael Bailon-Ruiz
Magali Barbier
Christophe Grand

Performing a complex autonomous mission with a multi-robot system requires to integrate several deliberative approaches to perform task allocation, optimization, and execution control. Implementing such a deliberative architecture is a complex task: it requires the developer to master the decision algorithms themselves (e. g. , automated planning models), to have a good knowledge of the involved robotic platforms, and to think about how these elements will be assembled as a system architecture. We propose a framework to help designing such deliberative architectures. The framework relies on the concept of a hierarchical structure of actors, each actor managing goals with specific planning or optimization approaches, and delegating sub-goals to other actors.

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YNICL Journal 2021 Journal Article

Multiparametric in vivo analyses of the brain and spine identify structural and metabolic biomarkers in men with adrenomyeloneuropathy

Isaac M. Adanyeguh
Xiaofang Lou
Eavan McGovern
Marie-Pierre Luton
Magali Barbier
Elise Yazbeck
Romain Valabregue
Dinesh Deelchand

Objective Progressive myelopathy causes severe handicap in men with adrenomyeloneuropathy (AMN), an X-linked disorder due to ABCD1 pathogenic variants. At present, treatments are symptomatic but disease-modifying therapies are under evaluation. Given the small effect size of clinical scales in AMN, biomarkers with higher effect size are needed. Here we used high-resolution magnetic resonance techniques to identify non-invasive in vivo biomarkers of the brain and spine with high effect sizes. Methods We performed a multiparametric imaging and spectroscopy study in 23 male patients with AMN (age: 44 ± 11) and 23 male controls (age: 43 ± 11) of similar age and body-mass index. We combined (i) macrostructural analyses of the spine, using cross-sectional area (CSA) and magnetization transfer ratio (MTR), (ii) microstructural analyses of the spine and the brain, using diffusion tensor and the newly developed fixel-based analysis, and (iii) advanced metabolic analyses of the spine using metabolite cycling coupled to a semi-LASER sequences. Results Macrostructural alterations (decrease in CSA and MTR) were observed in patients at all spinal cord levels studied (C1-T2 for CSA and C1-C5 for MTR) (p < 0. 001). Microstructural alterations were observed in the spine and brain on diffusion tensor and fixel-based metrics though the latter showed higher effect sizes. Metabolic alterations were observed in patients as a decreased total N-acetylaspartate/myo-inositol ratio (p < 0. 001). Overall, MTR showed the highest effect size. Conclusion This cross-sectional study supports the use of multiparametric techniques that elucidate the structural, microstructural and metabolic alterations in AMN. These outcome measures should be tested longitudinally and in clinical trials.

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ICRA Conference 2018 Conference Paper

Integrating Planning and Execution for a Team of Heterogeneous Robots with Time and Communication Constraints

Patrick Bechon
Magali Barbier
Christophe Grand
Simon Lacroix
Charles Lesire
Cédric Pralet

Field multi-robot missions face numerous unavoidable disturbances, such as delays in executing tasks and intermittent communications. Coping with such disturbances requires to endow the robots with high-level decision skills. We present a distributed decision architecture based first on a hybrid planner that can manage decentralized repairs with partial communication, and secondly on a distributed execution algorithm that efficiently propagates delays. This architecture has been successfully experimented on the field for the achievement of surveillance missions involving eight (8) real autonomous aerial and ground robots.

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IROS Conference 2013 Conference Paper

HiDDeN: Cooperative plan execution and repair for heterogeneous robots in dynamic environments

Thibault Gateau
Charles Lesire
Magali Barbier

This paper presents HiDDeN, a high-level distributed architecture for multi-robot cooperation. HiDDeN aims at controlling a team of heterogeneous robots in environments with uncertain communications. It relies on a mission plan defined as an instantiated HTN, i. e. a hierarchical decomposition of robots' tasks. This hierarchical structure also benefits to plan repair operations in case of failure detections. This repair is made as local as possible, in order to avoid unnecessary communications between robots.

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