Analyse du contexte à l'aide de méthodes probabilistes pour l'interaction hommes-robots

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Navigating and exploring the surfaces of bodies of water allow swimming robots to perform a range of measurements while efficiently communicating and harvesting energy from the Sun. Such environments are often highly unstructured and cluttered with plant m ...

The gut-microbiota-brain axis influences neuroinflammation, neural development and behaviour such as sociability, memory and anxiety. To study these traits in vivo, especially during development or disease, it is crucial to analyse them over time and with ...

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

Objective. Vision restoration approaches, such as prosthetics and optogenetics, provide visual perception to blind individuals in clinical settings. Yet their effectiveness in daily life remains a challenge. Stereotyped quantitative tests used in clinical ...

Given the patchy nature of gas plumes and the slow response of conventional gas sensors, the use of mobile robots for Gas Source Localization (GSL) tasks presents significant challenges. These aspects increase the difficulties in obtaining gas measurements ...

We focus on distinctive data-driven measures of the fate of ongoing epidemics. The relevance of our pursuit is suggested by recent results proving that the short-term temporal evolution of infection spread is described by an epidemicity index related to th ...

With recent innovations in artificial intelligence (AI), machines can now recognize architectural patterns and generate new forms in ways that far exceed human capacity. The integration of machines in the design process has ushered in a substantial shift i ...

Robots outside of the fenced factories have to deal with continuously changing environment, this requires fast and flexible modes of control. Planning methods or complex learning models can find optimal paths in complex surroundings, but they are computati ...

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 ...

Navigation of drones is predominantly based on sensor fusion algorithms. Most of these algorithms make use of some form of Bayesian filtering with a majority employing an Extended Kalman Filter (EKF), wherein inertial measurements are fused with a Global N ...

Biohybrid systems in which robotic lures interact with animals have become compelling tools for probing and identifying the mechanisms underlying collective animal behavior. One key challenge lies in the transfer of social interaction models from simulatio ...

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 ...

Learning manipulation from demonstration is a key way for humans to teach complex tasks. However, this domain mainly focuses on kinetic teaching, and does not consider imitation of interaction forces which is essential for more contact rich tasks. We propo ...

Modular robotics link the reliability of a centralised system with the adaptivity of a decentralised system. It is difficult for a robot with a fixed shape to be able to perform many different types of tasks. As the task space grows, the number of functi ...

In various robotics applications, the selection of function approximation methods greatly influences the feasibility and computational efficiency of algorithms. Tensor Networks (TNs), also referred to as tensor decomposition techniques, present a versatile ...

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 ...

Low-level light detection with high spatial and timing accuracy is a growing area of interest by virtue of applications such as light detection and ranging (LiDAR), biomedical imaging, time-resolved Raman spectroscopy, and quantum applications. Single-phot ...

Accurate forecasting of photovoltaic (PV) power production is crucial for the integration of more renewable energy sources into the power grid. PV power production is highly intermittent, due to the stochastic cloud behaviour and cloud dynamics. Previous w ...

While road obstacle detection techniques have become increasingly effective, they typically ignore the fact that, in practice, the apparent size of the obstacles decreases as their distance to the vehicle increases. In this letter, we account for this by c ...

Environmental monitoring and mapping operations are an essential tool to combat climate change. An important branch of this domain concerns the construction of reliable gas maps. Adaptive navigation strategies coupled with multi-robot systems improve the o ...

Analyse du contexte à l'aide de méthodes probabilistes pour l'interaction hommes-robots

Chat with Graph Search

Highly agile flat swimming robot

Assessment of neurobehavioural traits under gnotobiotic conditions: an approach for multiple analyses in the same mouse

Aggregating Spatial and Photometric Context for Photometric Stereo

Wide-angle simulated artificial vision enhances spatial navigation and object interaction in a naturalistic environment

Sense in Motion with Belief Clustering: Efficient Gas Source Localization with Mobile Robots

Epidemicity indices and reproduction numbers from infectious disease data in connected human populations

Deep Architectural Form

Exact Obstacle Avoidance for Robots in Complex and Dynamic Environments Using Local Modulation

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VDMNav: Software Architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones

Quantifying the biomimicry gap in biohybrid robot-fish pairs

Gas Sensing with Rotary-Wing Nano Aerial Vehicles

Learning Motion Reconstruction from Demonstration via Multi-Modal Soft Tactile Sensing

Memento Mori: Reliable robustness in self-reconfigurable modular robots

Robot Learning using Tensor Networks

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

Advanced Silicon and SWIR Single-Photon Avalanche Diodes: Design, Simulation, and Characterization

Network time series forecasting in photovoltaics power production

Perspective Aware Road Obstacle Detection

Multi-Robot 3D Gas Distribution Mapping: Coordination, Information Sharing and Environmental Knowledge