Ezequiel Leonardo Di Mario

Cette personne n’est plus à l’EPFL

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Publications associées (15)

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

The Effect of the Environment in the Synthesis of Robotic Controllers: A Case Study in Multi-Robot Obstacle Avoidance using Distributed Particle Swarm Optimization

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. While in simple environments it is usually straightforward for human designers to foresee the different conditions a robot will be exposed ...

MIT Press2013

A Comparison of PSO and Reinforcement Learning for Multi-Robot Obstacle Avoidance

Alcherio Martinoli, Zeynab Talebpour, Ezequiel Leonardo Di Mario

The design of high-performing robotic controllers constitutes an example of expensive optimization in uncertain environments due to the often large parameter space and noisy performance metrics. There are several evaluative techniques that can be employed ...

IEEE2013

A Trajectory-based Calibration Method for Stochastic Motion Models

Alcherio Martinoli, Massimo Mastrangeli, Grégory Mermoud, Ezequiel Leonardo Di Mario

In this paper, we present a quantitative, trajectory-based method for calibrating stochastic motion models of water-floating robots. Our calibration method is based on the Correlated Random Walk (CRW) model, and consists in minimizing the Kolmogorov-Smirno ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

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The Effect of the Environment in the Synthesis of Robotic Controllers: A Case Study in Multi-Robot Obstacle Avoidance using Distributed Particle Swarm Optimization

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

MIT Press2013

A Trajectory-based Calibration Method for Stochastic Motion Models

Alcherio Martinoli, Massimo Mastrangeli, Grégory Mermoud, Ezequiel Leonardo Di Mario

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011