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Publications associées (30)

On the Scalability of Vision-based Drone Swarms in the Presence of Occlusions

Dario Floreano, Fabian Maximilian Schilling, Enrica Soria

Vision-based drone swarms have recently emerged as a promising alternative to address the fault-tolerance and flexibility limitations of centralized and communication-based aerial collective systems. Although most vision-based control algorithms rely on th ...

2022

A Critical Re-evaluation of Neural Methods for Entity Alignment

Robert West, Akhil Arora, Manuel Leone, Alberto Garcia Duran, Stefano Huber

Neural methods have become the de-facto choice for the vast majority of data analysis tasks, and entity alignment (EA) is no exception. Not surprisingly, more than 50 different neural EA methods have been published since 2017. However, surprisingly, an ana ...

ASSOC COMPUTING MACHINERY2022

Vision-based Flocking in Aerial Robot Swarms

Fabian Maximilian Schilling

Aerial robot swarms have the potential to perform time-critical and dangerous tasks such as disaster response without compromising human safety. However, their reliance on external infrastructure such as global positioning for localization and wireless net ...

EPFL2022

Model Predictive Control of Aerial Swarms

Enrica Soria

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

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. ...

2022

Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction

Mathieu Salzmann, Wei Mao

We introduce the task of action-driven stochastic human motion prediction, which aims to predict multiple plausible future motions given a sequence of action labels and a short motion history. This differs from existing works, which predict motions that ei ...

IEEE COMPUTER SOC2022

Dual-function engineering to construct ultra-stable anodes for potassium-ion hybrid capacitors: N, O-doped porous carbon spheres

Kangning Zhao, Yanan Chen, Chao Yang, Jie Xu, Xin Peng, Wen Liu, Wei Zhou

Heteroatom doping engineering is deemed to be an adoptable strategy to boost the potassium (K) storage performance of carbonaceous materials. The inevitable issue for this strategy lies in the huge volume expansion originated from the large radius of K+. I ...

Elsevier2022

Tales from a Robotic World. How Intelligent Machines Will Shape Our Future

Dario Floreano, Nicola Nosengo

Stories from the future of intelligent machines—from rescue drones to robot spouses—and accounts of cutting-edge research that could make it all possible. Tech prognosticators promised us robots—autonomous humanoids that could carry out any number of tasks ...

MIT Press2022

Microscopic field theory for structure formation in systems of self-propelled particles with generic torques

Ignacio Pagonabarraga Mora, Elena Sesé Sansa

We derive a dynamical field theory for self-propelled particles subjected to generic torques and forces by explicitly coarse-graining their microscopic dynamics, described by a many-body Fokker-Planck equation. The model includes both intrinsic torques ind ...

AIP Publishing2022

Collective behavior and emerging patterns in dense dry aligning active matter

Elena Sesé Sansa

In this thesis, we study systems of active particles interacting via generic torques of different nature. We analyze the phase behavior of these systems, which results from the interplay between self-propulsion, excluded-volume and torques. We tackle the p ...

EPFL2022

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2022

Collective behavior and emerging patterns in dense dry aligning active matter

Elena Sesé Sansa

EPFL2022

Dual-function engineering to construct ultra-stable anodes for potassium-ion hybrid capacitors: N, O-doped porous carbon spheres

Kangning Zhao, Yanan Chen, Chao Yang, Jie Xu, Xin Peng, Wen Liu, Wei Zhou

Elsevier2022