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Extension of a Ground Control Interface for Swarms of Small Drones

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Shape-changing robots adapt their own morphology to address a wider range of functions or environments than is possible with a fixed or rigid structure. Akin to biological organisms, the ability to alter shape or configuration emerges from the underlying m ...

Berlin2023

Human-Robot Swarm Interaction: An Explorative Path to Foster Complex Systems Understanding

Hala Khodr

Order, regularities, and patterns are ubiquitous around us. A flock of birds maneuvering in the sky, the self-organization of social insects, a global pandemic or a traffic jam are examples of complex systems where the macroscopic patterns arise from the m ...

EPFL2023

Swarms of flying robots in unknown environments

Enrica Soria

An optimal planning algorithm enables swarms of flying robots to explore unknown environments autonomously and safely. ...

AMER ASSOC ADVANCEMENT SCIENCE2022

Aerial robot swarms can have a large socio-economic impact. They can perform time-critical missions faster than a single robot and access dangerous environments without compromising human safety. However, swarm deployment is often limited to free environme ...

EPFL2022

Cellulan World: Interactive Platform to Learn Swarm Behaviors

Pierre Dillenbourg, Barbara Bruno, Hala Khodr, Aditi Kothiyal

Swarming behaviors are ubiquitous in nature, and an important topic to teach and learn. In the learning sciences domain of complex systems understanding, studies have shown that novices tend to assume that centralized control and leadership should exist wh ...

IFAAMAS2022

Predictive control of aerial swarms in cluttered environments

Dario Floreano, Fabrizio Schiano, Enrica Soria

Classical models of aerial swarms often describe global coordinated motion as the combination of local interactions that happen at the individual level. Mathematically, these interactions are represented with potential fields. Despite their explanatory suc ...

2021

SwarmLab: a MATLAB Drone Swarm Simulator

Dario Floreano, Fabrizio Schiano, Enrica Soria

Among the available solutions for drone swarm simulations, we identified a lack of simulation frameworks that allow easy algorithms prototyping, tuning, debugging and performance analysis. Moreover, users who want to dive in the research field of drone swa ...

2020

Kernel methods and Model predictive approaches for Learning and Control

Sanket Sanjay Diwale

Data-driven modeling and feedback control play a vital role in several application areas ranging from robotics, control theory, manufacturing to management of assets, financial portfolios and supply chains. Many such problems in one way or another are rela ...

EPFL2019

Extension of a ground control interface for swarms of Small Drones

Dario Floreano, Grégoire Hilaire Marie Heitz, Nicolas Dousse

Although the technology for fully autonomous swarms of robots is rapidly progressing, the human operator will continue to play an important role during any swarming mission due to safety, monitoring and control constraints. In this paper, we present the se ...

Springer2016

Stochastic learning and control in multiple coordinate systems

Sylvain Calinon

A probabilistic interpretation of model predictive control is presented, enabling extensions to multiple coordinate systems. The resulting controller follows a minimal intervention principle, by learning and retrieving movements through the coordination of ...

2016