Publications by Dario Floreano

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Evolutionary robotics is a new technique for the automatic creation of autonomous robots. Inspired by the Darwinian principle of selective reproduction of the fittest, it views robots as autonomous artificial organisms that develop their own skills in close interaction with the environment and without human intervention. Drawing heavily on biology and ethology, it uses the tools of neural networks, genetic algorithms, dynamic systems, and biomorphic engineering. The resulting robots share with simple biolog

In this paper we address the problem of defining a measure of diversity for a population of individuals whose genome can be subjected to major reorganizations during the evolutionary process. To this end, we introduce a measure of diversity for populations of strings of variable length defined on a finite alphabet, and from this measure we derive a semi-metric distance between pairs of strings. The definitions are based on counting the number of substrings of the strings, considered first separately and the

In most animal species, vision is mediated by compound eyes, which offer lower resolution than vertebrate single-lens eyes, but significantly larger fields of view with negligible distortion and spherical aberration, and high temporal resolution in a tiny ...

Evolutionary algorithms are widespread heuristic methods inspired by natural evolution to solve difficult problems for which analytical approaches are not suitable. In many domains experimenters are not only interested in discovering optimal solutions, but ...

Human-Robot Interfaces (HRIs) represent a crucial component in telerobotic systems. Body-Machine Interfaces (BoMIs) based on body motion can feel more intuitive than standard HRIs for naive users as they leverage humans’ natural control capability over the ...

Collective behaviour enhances environmental sensing and decision-making in groups of animals. Experimental and theoretical investigations of schooling fish, flocking birds and human crowds have demonstrated that simple interactions between individuals can ...

Numerous methods have been developed for inference of gene regulatory networks from expression data, however, their strengths and weaknesses remain poorly understood. Accurate and systematic evaluation of these methods is hampered by the difficulty of constructing adequate benchmarks and the lack of tools for a differentiated analysis of network predictions on such benchmarks. Here, we present the new version (3.0) of GeneNetWeaver (GNW), an open-source tool for in silico benchmark generation and performanc

In this article we describe a methodology for evolving neurocontrollers of autonomous mobile robots without human intervention. The presentation, which spans from technological and methodological issues to several experimental results on evolution of physical mobile robots, covers both previous and recent work in the attempt to provide a unified picture within which the reader can compare the effects of systematic variations on the experimental settings. After describing some key principles for building mob

From perception to action and form action to perception, all elements of an autonomous agent are interdependent and need to be strongly coherent. The final behavior of the agent is the result of the global activity of this loop and every weakness of incoherence of a single element has strong consequences on the performances of the agent. We think that, for the purpose of building autonomous robots, all these elements need to be developed together in continuous interaction with the environment. We describe t

The efficiency of social insect colonies critically depends on their ability to efficiently allocate workers to the various tasks which need to be performed. While numerous models have investigated the mechanisms allowing an efficient colony response to ex ...

In this paper, we describe the artificial evolution of adaptive neural controllers for an outdoor mobile robot equipped with a mobile camera. The robot can dynamically select the gazing direction by moving the body and/or the camera. The neural control sys ...

We describe an incremental approach towards the development of autonomous indoor flyers that use only vision to navigate in textured environments. In order to cope with the severe weight and energy constraints of such systems, we use spiking neural controllers that can be implemented in tiny micro-controllers and map visual information into motor commands. The network morphology is evolved by means of an evolutionary process on the physical robots. This methodology is tested in three robots of increasing co

Artiﬁcial neural networks, electronic circuits, and gene networks are some examples of systems that can be modeled as networks, that is, as collections of interconnected nodes. In this paper we introduce the concept of terminal graph (t-graph for short), w ...

In the last few years several researchers have resorted to artificial evolution (e.g. genetic algorithms) and learning techniques (e.g. neural networks) for studying the interaction between learning and evolution. These studies have been conducted for two different purposes: (a) looking at the performance advantages obtained by combining these two adaptive techniques; (b) understanding the role of the interaction between learning and evolution in biological organisms. In this paper we describe some of the m

A large class of systems of biological and technological relevance can be described as analog networks, that is, collections of dynamical devices interconnected by links of varying strength. Some examples of analog networks are genetic regulatory networks, ...

Artificial evolution of computer software (evolutionary neural networks, genetic programming, evolutionary fuzzy systems, etc.) has been shown to generate software that in many cases is more performant than that designed by engineers. Evolved software performs well under the same conditions used during evolutionary training. However, in situations where unpredictable change may affect normal operation, evolved systems often fail. In this paper we describe a new approach for evolving software that remains ad

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circu ...

The control of collective robotic systems, such as drone swarms, is often delegated to autonomous navigation algorithms due to their high dimensionality. However, like other robotic entities, drone swarms can still benefit from being teleoperated by human ...

Minimally invasive surgeries, such as cardiac ablations, increasingly resort to magnetically-steered catheters. To enhance the dexterity and tissue interaction capabilities of these devices, researchers have developed catheters with variable stiffness (VS) ...

The design and control of winged aircraft and drones is an iterative process aimed at identifying a compromise of mission-specific costs and constraints. When agility is required, shape-shifting (morphing) drones represent an efficient solution. However, m ...

Dario Floreano

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Evolutionary Robotics. The Biology, Intelligence, and Technology of Self-organizing Machines

Measures of Diversity for Populations and Distances Between Individuals with Highly Reorganizable Genomes

Miniature curved artificial compound eyes

Artificial Evolution by Viability Rather Than Competition

Does spontaneous motion lead to intuitive Body-Machine Interfaces? A fitness study of different body segments for wearable telerobotics

Mechanosensory interactions drive collective behaviour in Drosophila

GeneNetWeaver 3.0: realistic benchmark generation and performance profiling of network inference methods

Evolutionary Neurocontrollers for Autonomous Mobile Robots

Evolution of neural control structures: Some experiments on mobile robots

Division of labour and colony efficiency in social insects: effects of interactions between genetic architecture, colony kin structure and rate of perturbations

Active Vision and Receptive Field Development in Evolutionary Robots

Vision-based Navigation from Wheels to Wings

Beyond Graphs: A New Synthesis

Learning and Evolution

The Age of Analog Networks

Artificial Evolution of Adaptive Software: An Application to Autonomous Robots

Fluctuation-driven neural dynamics reproduce Drosophila locomotor patterns

Personalized Human-Swarm Interaction Through Hand Motion

Rapid and Continuous Stiffness Control of Fiber-Jamming Catheters for Cardiac Ablation

Co-Design Optimisation of Morphing Topology and Control of Winged Drones