Contributions to the modeling and design of reconfigurable reflecting cells embedding discrete control elements

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Publications associées (31)

A Distributed Noise-Resistant Particle Swarm Optimization Algorithm for High-Dimensional Multi-Robot Learning

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

Population-based learning techniques have been proven to be effective in dealing with noise in numerical benchmark functions and are thus promising tools for the high-dimensional optimization of controllers for multiple robots with limited sensing capabili ...

2015

Distributed Multi-Robot Learning using Particle Swarm Optimization

Ezequiel Leonardo Di Mario

This thesis studies the automatic design and optimization of high-performing robust controllers for mobile robots using exclusively on-board resources. Due to the often large parameter space and noisy performance metrics, this constitutes an expensive opti ...

EPFL2015

A production scheduling problem with uncertain sequence-dependent set-up times and random yield

Paul Xirouchakis, Byung Jun Joo

A scheduling problem in a real production line with uncertain sequence-dependent set-up times and a random yield is considered. The production line can produce multiple product types as production lots, each of which is composed of a number of products of ...

Taylor & Francis Ltd2015

Distributed vs. Centralized Particle Swarm Optimization for Learning Flocking Behaviors

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

In this paper we address the automatic synthesis of controllers for the coordinated movement of multiple mobile robots. We use a noise-resistant version of Particle Swarm Optimization to learn in simulation a set of 50 weights of a plastic artificial neura ...

The MIT Press2015

Ant Metaheuristic with Adapted Personalities for the Vehicle Routing Problem

Nicolas Zufferey, Rémy Glardon, Jaime Farres

At each generation of an ant algorithm, each ant builds a solution step by step by adding an element to it. Each choice is based on the greedy force (short term profit or heuristic information) and the trail system (central memory which collects informatio ...

Springer Int Publishing Ag2015

Role of Compliance on the Locomotion of a Reconfigurable Modular Snake Robot

Auke Ijspeert, Stéphane Bonardi, Massimo Vespignani, Kamilo Andres Melo Becerra

This paper presents the results of a study on the effect of in-series compliance on the locomotion of a simulated 8-DoF Lola-OP Modular Snake Robot with added compliant elements. We explore whether there is an optimal stiffness for gait, terrain type, or s ...

2015

Ant Metaheuristics with Adapted Personalities for Vehicle Routing Problem

Nicolas Zufferey, Rémy Glardon, Jaime Farres

2015

A mixed-signal computer architecture and its application to power system problems

Theodoros Kyriakidis

Radical changes are taking place in the landscape of modern power systems. This massive shift in the way the system is designed and operated has been termed the advent of the ``smart grid''. One of its implications is a strong market pull for faster power ...

EPFL2015

Distributed Particle Swarm Optimization for limited-time adaptation with real robots

Alcherio Martinoli, Ezequiel Leonardo Di Mario

Evaluative techniques offer a tremendous potential for online controller design. However, when the optimization space is large and the performance metric is noisy, the overall adaptation process becomes extremely time consuming. Distributing the adaptation ...

2014

Analysis of Fitness Noise in Particle Swarm Optimization: From Robotic Learning to Benchmark Functions

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

Population-based learning techniques have been proven to be effective in dealing with noise and are thus promising tools for the optimization of robotic controllers, which have inherently noisy performance evaluations. This article discusses how the result ...

2014

The Role of Environmental and Controller Complexity in the Distributed Optimization of Multi-Robot Obstacle Avoidance

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

The ability to move in complex environments is a fundamental requirement for robots to be a part of our daily lives. Increasing the controller complexity may be a desirable choice in order to obtain an improved performance. However, these two aspects may p ...

2014

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