RoboGen: Robot Generation through Artificial Evolution

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Social insects, such as ants, termites, and honeybees, have evolved sophisticated societies where the collaborative efforts of "simple" individuals can lead to the emergence of complex dynamics. The reliance of each organism on the collective is so great t ...

Harmful chemical compounds are released daily in warehouses, chemical plants and during environmental emergencies. Their uncontrolled dispersion contributes to the pollution of the atmosphere and threatens human and animal lives. When gas leaks occur, the ...

We report a soft actuator that generates continuous rotation of an object placed on it by electromagnetically exciting circular travelling waves in a soft disk. The disk, that serves as the stator, is made of a stretchable composite consisting of segments ...

This doctoral thesis navigates the complex landscape of motion coordination and formation control within teams of rotary-wing Micro Aerial Vehicles (MAVs). Prompted by the intricate demands of real-world applications such as search and rescue or surveillan ...

Here, we introduce a design, fabrication, and control methodology for large amplitude torsional microactuators powered by ultrasound. The microactuators are 3D printed from two polymers with drastically different elastic moduli as a monolithic compliant me ...

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

This article summarizes the recent advancements in the design, fabrication, and control of microrobotic devices for the diagnosis and treatment of brain disorders. With a focus on diverse actuation methods, we discuss how advancements in materials science ...

This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...

Advancing quantum technologies depends on the precise control of individual quantum systems, the so-called qubits, and the exploitation of their quantum properties. Nowadays, expanding the number of qubits to be entangled is at the core of the developments ...

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

Despite their incredible performance, it is well reported that deep neural networks tend to be overoptimistic about their prediction confidence. Finding effective and efficient calibration methods for neural networks is therefore an important endeavour tow ...

There is a growing trend towards designing learning activities featuring robots as collaborative exercises where children work together to achieve the activity objectives, generating interactions that can trigger learning processes. Witnessing such activit ...

RoboGen: Robot Generation through Artificial Evolution

Chattez avec Graph Search

A Biohybrid Superorganism - Investigating honeybees' collective behaviors via interactive robotics

Gas Sensing with Rotary-Wing Nano Aerial Vehicles

Permanently magnetized elastomer rotating actuator using traveling waves

Distributed Predictive Formation Control of Autonomous Rotary-Wing Micro Aerial Vehicles

3D printed large amplitude torsional microactuators powered by ultrasound

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Small-scale robotic devices for medical interventions in the brain

Partial discharge localization in power transformer tanks using machine learning methods

Electron-beam based nanoscale quantum controls

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Expectation consistency for calibration of neural networks

Computational Models of Mutual Understanding for Human-Robot Collaborative Learning