Cette communication vise à présenter un atelier pédagogique en cours de développement s’appuyant sur les outils de recherche développés dans le cadre de la thèse de Laetitia Bornes intitulée « Méthodes et outils systémiques concrets pour faire face à la complexité environnementale et aux effets rebond pendant un processus de design ou de décision » [1]. La version actuelle de l’atelier a été conçue à destination d’étudiants en cursus ingénieur ou scientifique, et s’inscrit dans des enseignements portant sur la conception de produits ou de services. L’atelier est pensé comme une introduction à la modélisation systémique par le biais de l’analyse des « effets rebond » (ou...

<div><p>The precise identification of terminal area arrival procedures is crucial for airspace planning, traffic management, and safety analysis. Traditional methods are limited in automatically detecting specific procedural maneuvers from large amounts of trajectory data. This paper proposes a methodology with knowledge-based filtering to automatically identify three common air traffic control arrival procedures, namely Point Merge System, Vector for Space, and Trombone, from historical trajectory data. After clustering the landing trajectories in the terminal area, we identify the predominant flight patterns. Then, a knowledge-based filtering algorithm, designed based...

The OpenGeoDrone is a technical project that aims at providing an open-source and open hardware design of a vertical take-off and landing (VTOL) uncrewed aerial vehicle (UAV) system for the research community. Its operational characteristics have been established in the context of high-mountain glacier and atmosphere observations, part of the FlyHigh project. The main contribution is an end-to-end design and manufacturing approach based on parametric OpenSCAD geometry and mixed additive manufacturing processes: classical Polyethylene Terephthalate Glycol (PETG) printing for structural and impact-prone components, and polylactic acid (PLA) Aero spiral-vase printing for...

n Michael Crichton’s Prey, a cloud of nano-robots escapes human control and becomes something far more unsettling than a machine. It stretches, contracts, reorganizes, and even hunts. It behaves like a living swarm endowed with a form of collective intelligence, even though no single unit possesses a brain (see Striking image). The story was fiction, yet it captured an idea that has become increasingly important in complexity science. When many simple agents interact locally, complex and sometimes surprising behavior can emerge at the level of the group.

In firefighting, aerial robots (a.k.a drones) are primarily used as remote sensors, leaving their potential to actively support firefighters unrealized. We propose FireFly, a mini drone designed to serve as an interactive teammate, providing on-the-go support during indoor firefighting tasks. For example, during reconnaissance, FireFly can locate victims and guide firefighters to their position. We present a proof-of-concept built with lowcost off-the-shelf hardware, combining gestural interaction and visual feedback on a low-resolution display, which was iteratively designed. We evaluate Firefly in a user study with professional and volunteer firefighters, who performed...

Smoke dynamics is notoriously challenging for both the physics and machine learning communities due to the tight coupling between the underlying physics and light-smoke interactions. Existing learning-based simulators typically rely on large-scale simulated data for 2D problems, which cannot be scaled efficiently and require an external physics-based simulators. Consequently, previous work on smoke cloud has mostly been restricted to reconstruction, while forecasting is either limited to visual appearance alone, or relies on external ground truth data. In this paper, we address these limitations by tackling the unsupervised learning of 3D smoke cloud simulations directly...

We investigate the evolution of the reliability of a mobile communication network through its capacity to avoid and withstand faults (called robustness) and to maintain proper functioning if faults occur nevertheless (called resilience). Our case study focuses on a swarm of nanosatellites orbiting the Moon and operating as a distributed space interferometer. The objective of this study is to evaluate the impact of graph division techniques on the robustness and resilience of the system, simultaneously. A high reliability level is key to guaranteeing proper quality of service by recovering from impairments while preserving the primary function or mission of the mobile...

As a core concept in Industry 4.0, Cyber-Physical Systems (CPS) have been widely utilized in both academic and industrial projects. By leveraging engineered swarm system and mobility, groups of CPS, such as drone swarms, robotic teams, or satellite constellations, can interact and cooperate to collectively exhibit swarm intelligence characterized by adaptability, robustness, and scalability. As a distinct class of computing platforms, CPS swarms face significant challenges in achieving such intelligence. For instance, the dynamic interactions between mobile devices and their environments introduce high uncertainty in system management. In addition, exposure to harsh...

<div><p>Active brain-computer interfaces (aBCIs) exhibit substantial performance variability both across and within participants. While many sources of variability have been investigated, circadian influences remain largely unexplored in aBCI control. We investigated whether time of day and chronotype (individual's circadian preference for sleep and activity timing across the day) jointly modulate BCI performance (classification accuracy). Twelve participants completed 6 EEGbased BCI sessions each alternating between morning and afternoon sessions, performing 3 mental tasks (motor imagery, mental calculation, letter/word association). Online performance was analyzed using...