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

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Distributed Graph-based Convoy Control for Networked Intelligent Vehicles

Alcherio Martinoli, Ali Marjovi, Milos Vasic, Joseph Chadi Benoit Lemaitre

This paper presents an approach for formation control of multi-lane vehicular convoys in highways. We extend a Laplacian graph-based, distributed control law such that networked intelligent vehicles can join or leave the formation dynamically without jeopa ...

IEEE2015

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The integration of weather forecasts and demand prediction into the energy management system of buildings is usually achieved using a model-based predictive control. The performance of such control techniques strongly depends on the accuracy of the thermal ...

2015

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 ...

Cambridge University Press2014

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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

Distributed Learning of Cooperative Robotic Behaviors using Particle Swarm Optimization

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

In this paper we study the automatic synthesis of robotic controllers for the coordinated movement of multiple mobile robots. The algorithm used to learn the controllers is a noise-resistant version of Particle Swarm Optimization, which is applied in two d ...

2014

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The design of efficient locomotion controllers for arbitrary structures of reconfigurable modular robots is challenging because the morphology of the structure can change dynamically during the completion of a task. In this paper, we propose a new method t ...

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

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The ability to move in complex environments is a fundamental requirement for robots to be a part of our daily lives. While in simple environments it is usually straightforward for human designers to foresee the different conditions a robot will be exposed ...

MIT Press2013

Evaluative techniques offer a tremendous potential for on-line controller design. However, when the optimization space is large and the performance metric is noisy, the time needed to properly evaluate candidate solutions becomes prohibitively large and, a ...

2012

The Particle Swarm Optimization (PSO) method and the Genetic Algorithm (GA) were used to derive formulas for determining the velocity and concentration profiles in sheet flows. Specifically, these evolutionary optimization algorithms were used in conjuncti ...

Asme-Amer Soc Mechanical Eng2012