Publications de Dario Floreano

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Evolutionary robotics - as other adaptive methods, such as reinforcement learning and learning classifier systems - can take considerable time and resources which require a careful evaluation of the hardware tools and methodologies employed. We outline a set of hardware solutions and working methodologies that can be used for successfully implementing and extending the evolutionary approach to complex environments, robots, and real-world applications. The issues discussed include the integration of simulati

Communication is an indispensable component of animal societies, yet many open questions remain regarding the factors affecting the evolution and reliability of signalling systems. A potentially important factor is the level of genetic relatedness between ...

Stories from the future of intelligent machines—from rescue drones to robot spouses—and accounts of cutting-edge research that could make it all possible. Tech prognosticators promised us robots—autonomous humanoids that could carry out any number of tasks ...

The operation of telerobotic systems can be a challenging task, requiring intuitive and efficient interfaces to enable inexperienced users to attain a high level of proficiency. Body-Machine Interfaces (BoMI) represent a promising alternative to standard c ...

Variable stiffness (VS) is an important feature that significantly enhances the dexterity of magnetic catheters used in minimally invasive surgeries. Existing magnetic catheters with VS consist of sensors, heaters, and tubular structures filled with low me ...

Co-evolution (i.e. the evolution of two or more competing populations with coupled fitness) has several interesting features that may potentially enhance the power of adaptation of artificial evolution. In particular, as discussed by Dawkins and Krebs [2], competing populations may reciprocally drive one another to increasing levels of complexity by producing an evolutionary “arms race”. In this paper we will investigate the role of co-evolution in the context of evolutionary robotics. In particular, we wil

Decentralized drone swarms deployed today either rely on sharing of positions among agents or detecting swarm members with the help of visual markers. This work proposes an entirely visual approach to coordinate markerless drone swarms based on imitation l ...

In search and rescue missions, Micro Air Vehicles (MAV's) can assist rescuers to faster locate victims inside a large search area and to coordinate their efforts. Acoustic signals play an important role in outdoor rescue operations. Emergency whistles, as ...

People learn motor activities best when they are conscious of their errors and make a concerted effort to correct them. While haptic interfaces can facilitate motor training, existing interfaces are often bulky and do not always ensure post-training skill ...

This article presents the first results of a project in underwater modular robotics, called Neubots. The goals of the projects are to explore, following Von Neumann’s ideas, potential mechanisms underlying self-organization and self-replication. We briefly ...

The evolution of artificial neural networks (ANNs) is often used to tackle difficult control problems. There are different approaches to the encoding of neural networks in artificial genomes. Analog Genetic Encoding (AGE) is a new implicit method derived f ...

In this paper I explore the hypothesis that some of today's robots might possess a form of consciousness whose substrate is a mere algorithm. First, consciousness is defined within an evolutionary framework as awareness of one's own state in relation to the external environment. Then, the basic prerequisites for such conscious activity are discussed, namely embodiment, autonomy, and adaptation mechanisms. Artificial evolution, rather than evolutionary optimisation, is presented as a viable methodology to cr

Localization is one of the key challenges that needs to be considered beforehand to design truly autonomous MAV teams. In this paper, we present a cooperative method to address the localization problem for a team of MAVs, where individuals obtain their pos ...

In this paper, we introduce a self-assembling and self-organizing artifact, called a swarm-bot, composed of a swarm of s-bots, mobile robots with the ability to connect to and to disconnect from each other. We discuss the challenges involved in controlling a swarm-bot and address the problem of synthesizing controllers for the swarm-bot using artificial evolution. Specifically, we study aggregation and coordinated motion of the swarm-bot using a physics-based simulation of the system. Experiments, using a s

Artificial neural networks are applied to many real-world problems, ranging from pattern classification to robot control. In order to design a neural network for a particular task, the choice of an architecture (including the choice of a neuron model), and ...

An aircraft's airspeed, angle of attack, and angle of side slip are crucial to its safety, especially when flying close to the stall regime. Various solutions exist, including pitot tubes, angular vanes, and multihole pressure probes. However, current sensors are either too heavy (> 30g) or require large airspeeds (>20 m/s), making them unsuitable for small uncrewed aerial vehicles. We propose a novel multihole pressure probe, integrating sensing electronics in a single-component structure, resulting in a m

There are not yet fully autonomous flying robots capable of maneuvering in small cluttered environments as insects do. The substantial weight and energy constraints typically encountered in this kind of robotic applications preclude the use of powerful processors and classical distance sensors. Moreover, due to their highly dynamic motion, flying systems require fast sensory-motor mapping. To pave the way toward fully autonomous indoor flying robots we take inspiration from flying insects like flies because

Edible robots and robotic food — edible systems that perceive, process and act upon stimulation — could open a new range of opportunities in health care, environmental management and the promotion of healthier eating habits. For example, they could enable ...

Designing optimal soft modular robots is difficult, due to non-trivial interactions between morphology and controller. Evolutionary algorithms (EAs), combined with physical simulators, represent a valid tool to overcome this issue. In this work, we investi ...

Perching in unmanned aerial vehicles (UAVs) offers the possibility of extending the range of aerial robots beyond the limits of their batteries. It has been a topic of intense study for multirotor UAVs. Perching in winged UAVs is harder because a kinetic e ...

Dario Floreano

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Hardware Solutions for Evolutionary Robotics

Relatedness influences signal reliability in evolving robots

Tales from a Robotic World. How Intelligent Machines Will Shape Our Future

The Impact of Virtual Reality and Viewpoints in Body Motion Based Drone Teleoperation

A Variable Stiffness Magnetic Catheter Made of a Conductive Phase-Change Polymer for Minimally Invasive Surgery

How co-evolution can enhance the adaptation power of artificial evolution: Implications for evolutionary robotics

Learning Vision-based Flight in Drone Swarms by Imitation

Robust Acoustic Source Localization of Emergency Signals from Micro Air Vehicles

Smart Textiles that Teach: Fabric‐Based Haptic Device Improves the Rate of Motor Learning

Co-evolution of Structures and Controllers for Neubot Underwater Modular Robots

Neuroevolution with Analog Genetic Encoding

Ago Ergo Sum

Audio-based Localization for Swarms of Micro Air Vehicles

Evolving Self-Organizing Behaviors for a Swarm-bot

Neuroevolution: from architectures to learning

Miniature Multihole Airflow Sensor for Lightweight Aircraft Over Wide Speed and Angular Range

Bio-inspired Indoor Microflyers

Towards edible robots and robotic food

Seeking Quality Diversity in Evolutionary Co-design of Morphology and Control of Soft Tensegrity Modular Robots

Passive Perching with Energy Storage for Winged Aerial Robots