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

Related publications (32)

Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

EPFL2024

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

Silvestro Micera, Simone Romeni

Objective. Peripheral nerve interfaces have the potential to restore sensory, motor, and visceral functions. In particular, intraneural interfaces allow targeting deep neural structures with high selectivity, even if their performance strongly depends upon ...

IOP Publishing Ltd2023

A comprehensive review of digital twin-part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives

Olga Fink

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision- and policy-making, and more, by comprehensively m ...

SPRINGER2023

Assisted specification of discrete choice models

Michel Bierlaire, Timothy Michael Hillel, Nicola Marco Ortelli

Determining appropriate utility specifications for discrete choice models is time-consuming and prone to errors. With the availability of larger and larger datasets, as the number of possible specifications exponentially grows with the number of variables ...

ELSEVIER SCI LTD2021

Optimization Methods for Control: From Embedded Programmable Hardware to Data-Driven Process Optimization

Harsh Ambarishkumar Shukla

The research community has been making significant progress in hardware implementation, numerical computing and algorithm development for optimization-based control. However, there are two key challenges that still have to be overcome for optimization-base ...

EPFL2021

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

Multi-well capture zones in strip-shaped aquifers

David Andrew Barry

Capture zone equations for a multi-well system in strip-shaped confined and unconfined aquifers with and without regional flow are presented. The aquifer is limited by two parallel boundaries that are either no flow (barrier) or inflow (variable head) so t ...

PUBLIC LIBRARY SCIENCE2020

The electric autonomous dial-a-ride problem

Claudia Bongiovanni

This thesis develops mathematical programming frameworks to operate electric autonomous vehicles in the context of ride-sharing services. The introduced problem is a novel variant of the Dial-a-Ride Problem (DARP), denoted by the electric Autonomous Dial-a ...

EPFL2020

Design and Calibration of a Lightweight Physics-Based Model for Fluid-Mediated Self-Assembly of Robotic Modules

Alcherio Martinoli, Hala Khodr, Bahar Haghighat

In this paper, we consider a system consisting of multiple floating robotic modules performing self-assembly. Faithfully modeling such a system and its inter-module interactions typically involves capturing the hydrodynamic forces acting on the modules usi ...

Springer2019

Modeling and Assessment of Urban Energy Systems

Amarasinghage Tharindu Dasun Perera

Improving the energy sustainability of our cities involves the integration of multiple renewable energy technologies into existing energy infrastructure, stretching the capabilities of traditional energy systems to the limit. To consider the transition tak ...

EPFL2019

Controlling the bias error of Fokker- Planck methods for rarefied gas dynamics simulations

Mohammadhossein Gorji

Direct simulation Monte-Carlo (DSMC) is the most established method for rarefied gas flow simulations. It is valid from continuum to near vacuum, but in cases involving small Knudsen numbers (Kn), it suffers from high computational cost. The Fokker-Planck ...

2019

Computational rule-based approach for corner correction of non-Manhattan geometries in mask aligner photolithography

Toralf Scharf, Wilfried Noell, Chen Yan, Raoul Kirner

In proximity mask aligner photolithography, diffraction of light at the mask pattern is the predominant source for image shape distortions such as line end shortening and corner rounding. One established method to mitigate the impact of diffraction is opti ...

2019

Leading the Blind : Automated Transistor-Level Modeling for FPGA Architects

Grace Zgheib

The design and development of innovative FPGA architectures hinge on the flexibility of its toolchain. Retargetable toolchains, like the Verilog-to-Routing (VTR) flow, have been developed to enable the testing of new FPGAs by mapping circuits onto easily-d ...

EPFL2017

Noise-Resistant Particle Swarm Optimization for the Learning of Robust Obstacle Avoidance Controllers using a Depth Camera

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

The Ranger robot was designed to interact with children in order to motivate them to tidy up their room. Its mechanical configuration, together with the limited field of view of its depth camera, make the learning of obstacle avoidance behaviors a hard pro ...

Ieee2016

Intearcting Brownian Swarms: Some Analytical Results

Max-Olivier Hongler, Guillaume Adrien Sartoretti

We consider the dynamics of swarms of scalar Brownian agents subject to local imitation mechanisms implemented using mutual rank-based interactions. For appropriate values of the underlying control parameters, the swarm propagates tightly and the distances ...

MDPI AG2016

Control of agent swarms in random environments

Guillaume Adrien Sartoretti

The collective dynamic behavior of large groups of interacting autonomous agents (swarms) have inspired much research in both fundamental and engineering sciences. It is now widely acknowledged that the intrinsic nonlinearities due to mutual interactions c ...

EPFL2016

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

Byung Jun Joo, Paul Xirouchakis

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

Distributed Particle Swarm Optimization using Optimal Computing Budget Allocation for Multi-Robot Learning

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

Particle Swarm Optimization (PSO) is a population-based metaheuristic that can be applied to optimize controllers for multiple robots using only local information. In order to cope with noise in the robotic performance evaluations, different re-evaluation ...

2015

Ant Metaheuristic with Adapted Personalities for the Vehicle Routing Problem

Rémy Glardon, Nicolas Zufferey

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