Search Results for author: Mario Coppola

Found 4 papers, 3 papers with code

A model-based framework for learning transparent swarm behaviors

1 code implementation9 Mar 2021 Mario Coppola, Jian Guo, Eberhard Gill, Guido C. H. E. de Croon

The framework is based on the automatic extraction of two distinct models: 1) a neural network model trained to estimate the relationship between the robots' sensor readings and the global performance of the swarm, and 2) a probabilistic state transition model that explicitly models the local state transitions (i. e., transitions in observations from the perspective of a single robot in the swarm) given a policy.

An autonomous swarm of micro flying robots with range-based relative localization

1 code implementation12 Mar 2020 Shushuai Li, Mario Coppola, Christophe De Wagter, Guido C. H. E. de Croon

Accurate relative localization is an important requirement for a swarm of robots, especially when performing a cooperative task.

Robotics Multiagent Systems

Provable Emergent Pattern Formation by a Swarm of Anonymous, Homogeneous, Non-Communicating, Reactive Robots with Limited Relative Sensing and no Global Knowledge or Positioning

no code implementations18 Apr 2018 Mario Coppola, Jian Guo, Eberhard K. A. Gill, Guido C. H. E. de Croon

We then formally show that these local states can only coexist when the global desired pattern is achieved and that, until this occurs, there is always a sequence of actions that will lead from the current pattern to the desired pattern.

Robotics

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