Publication

Distributed Scalable Multi-Robot Learning using Particle Swarm Optimization

Publications associées (31)

Soft robotics for farm to fork: applications in agriculture & farming

Josephine Anna Eleanor Hughes, Kai Christian Junge

Agricultural tasks and environments range from harsh field conditions with semi-structured produce or animals, through to post-processing tasks in food-processing environments. From farm to fork, the development and application of soft robotics offers a pl ...

Iop Publishing Ltd2024

Filiform Variable Stiffness Technologies for Medical Robotics

Yegor Piskarev

In recent years, soft robotics has surged in applications like wearables, drones, smart fabrics, and medical instruments. Due to their compliance, these devices excel in tasks demanding dexterity and adaptability, such as manipulation, locomotion, crash re ...

EPFL2024

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Philippe Schwaller, Jeff Guo

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

Amer Chemical Soc2024

Predicting the long-term collective behaviour of fish pairs with deep learning

Francesco Mondada, Alexandre Massoud Alahi, Vaios Papaspyros

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...

2024

3D printed large amplitude torsional microactuators powered by ultrasound

Mehdi Ali Gadiri, Mahmut Selman Sakar, Amit Yedidia Dolev, Junsun Hwang

Here, we introduce a design, fabrication, and control methodology for large amplitude torsional microactuators powered by ultrasound. The microactuators are 3D printed from two polymers with drastically different elastic moduli as a monolithic compliant me ...

2024

Scalable constrained optimization

Maria-Luiza Vladarean

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

EPFL2024

Frequency response of fiber reinforced DEAs

Yves Perriard, Yoan René Cyrille Civet, Thomas Guillaume Martinez, Stefania Maria Aliki Konstantinidi, Markus Koenigsdorff

Dielectric Elastomer Actuators (DEAs) have emerged as versatile and promising devices for a multitude of applications, including soft robotics, haptic interfaces, and artificial muscles. DEAs are an interesting soft actuator technology due to their high en ...

Society of Photo-Optical Instrumentation Engineers (SPIE)2024

VDMNav: Software Architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones

Jan Skaloud, Gabriel François Laupré

Navigation of drones is predominantly based on sensor fusion algorithms. Most of these algorithms make use of some form of Bayesian filtering with a majority employing an Extended Kalman Filter (EKF), wherein inertial measurements are fused with a Global N ...

2024

Social Opinion Formation and Decision Making Under Communication Trends

Ali H. Sayed, Virginia Bordignon, Mert Kayaalp

This work studies the learning process over social networks under partial and random information sharing. In traditional social learning models, agents exchange full belief information with each other while trying to infer the true state of nature. We stud ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Geometric Learning: Leveraging differential geometry for learning and control

Bernardo Fichera

In this thesis, we concentrate on advancing high-level behavioral control policies for robotic systems within the framework of Dynamical Systems (DS). Throughout the course of this research, a unifying thread weaving through diverse fields emerges, and tha ...

EPFL2024

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Arnout Jan J Devos

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

EPFL2024