Publications associées à An ensemble inverse optimal control approach for robotic task learning and adaptation

Publications associées (39)

Overcoming Distribution Shifts and Imbalance Challenges in Representation Learning for Deep Regression Models

Deep learning has shown remarkable potential for industrial applications, particularly in predictive maintenance and condition monitoring. A key challenge in this domain is prognostics, specifically predicting the Remaining Useful Life (RUL) of assets - a ...

EPFL2025

Sequential Reasoning with Socially Caused Beliefs

Mert Kayaalp

Machine learning and artificial intelligence methods have achieved remarkable success, matching and even surpassing human capabilities in various complex tasks. However, many demonstrations have generally neglected a critical part of the intelligence that ...

EPFL2025

Learning to Reason with Neural Networks: Principles and Methods

Aryo Lotfi Jandaghi

This thesis focuses on understanding and improving the reasoning capabilities of neural networks. It develops theoretical results and empirical analyses to uncover reasoning potential and limitations, leveraging these insights to guide the design of improv ...

EPFL2025

On the Perspectives of Image-to-Lidar Constraints in Dynamic Network Optimisation

Thibaut Stoltz, Jan Skaloud, Davide Antonio Cucci, Laurent Valentin Jospin, Kyriaki Mouzakidou

The evolution of airborne mapping witnesses the introduction of hybrid lidar-camera systems to enhance data collection, i.e. to obtain simultaneously high-density point-cloud and texture. Yet, the common adjustment of both optical data streams is a nontriv ...

International Society for Photogrammetry and Remote Sensing2025

A phase transition in diffusion models reveals the hierarchical nature of data

Matthieu Wyart, Alessandro Favero, Antonio Sclocchi

Understanding the structure of real data is paramount in advancing modern deep-learning methodologies. Natural data such as images are believed to be composed of features organized in a hierarchical and combinatorial manner, which neural networks capture d ...

National Academy of Sciences2025

K-space physics-informed neural network (k-PINN) for compressed spectral mapping and efficient inversion of vibrations in thin composite laminates

Olga Fink

The vibrational response of structural components carries valuable information about their underlying mechanical properties, health status and operational conditions. This underscores the need for the development of efficient physics-based inversion algori ...

Elsevier BV2025

Memento Mori: Reliable robustness in self-reconfigurable modular robots

Kevin Andrew Holdcroft

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 ...

EPFL2024

Robot Learning using Tensor Networks

Suhan Narayana Shetty

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 ...

EPFL2024

Soft Robotics: A Route to Equality, Diversity, and Inclusivity in Robotics

Josephine Anna Eleanor Hughes

Robotics is entering our daily lives. The discipline is increasingly crucial in fields such as agriculture, medicine, and rescue operations, impacting our food, health, and planet. At the same time, it is becoming evident that robotic research must embrace ...

Mary Ann Liebert, Inc2024

Hitting with Different Joints of a Robotic Manipulator

Aude Billard, Harshit Khurana

This paper builds up the skill of impact aware non prehensile manipulation through a hitting motion by allowing the robot arm to come in contact with the environment with parts other than its end effector. Hitting with other joints allows us to manipulate ...

2024

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

Rafael Botner Barmak

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 ...

EPFL2024

Small-scale robotic devices for medical interventions in the brain

Mahmut Selman Sakar, Lorenzo Francesco John Noseda

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 ...

2024

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

Izzet Kagan Erünsal

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 ...

EPFL2024

Biohybrid Superorganisms—On the Design of a Robotic System for Thermal Interactions With Honeybee Colonies

Louis Arnaud Vahé Piotet, Francesco Mondada, Rafael Botner Barmak, Robert Matthew Mills, Raphael Cherfan

Social insects, such as ants, termites, and honeybees, have evolved sophisticated societies where collaboration and division of labor enhance survival of the whole colony, and are thus considered “superorganisms”. Historically, studying behaviors involving ...

2024

Towards edible robots and robotic food

Dario Floreano, Jun Shintake, Bokeon Kwak, Markéta Pankhurst

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 ...

2024

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

Lukas Huber

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 ...

EPFL2024

Quantifying the biomimicry gap in biohybrid robot-fish pairs

Francesco Mondada, Vaios Papaspyros

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 ...

2024

Online Multicontact Receding Horizon Planning via Value Function Approximation

Sylvain Calinon, Teguh Santoso Lembono

Planning multicontact motions in a receding horizon fashion requires a value function to guide the planning with respect to the future, e.g., building momentum to traverse large obstacles. Traditionally, the value function is approximated by computing traj ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Avoidance of Concave Obstacles Through Rotation of Nonlinear Dynamics

Aude Billard, Lukas Huber

Controlling complex tasks in robotic systems, such as circular motion for cleaning or following curvy lines, can be dealt with using nonlinear vector fields. This article introduces a novel approach called the rotational obstacle avoidance method (ROAM) fo ...

Ieee-Inst Electrical Electronics Engineers Inc2024

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

Alcherio Martinoli, Wanting Jin

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 ...

2024