Publications associées à Learning Optimal Impedance Control During Complex 3D Arm Movements

Publications associées (37)

The Dawn of High-throughput and Genome-scale Kinetic Modeling: Recent Advances and Future Directions

Vassily Hatzimanikatis, Ljubisa Miskovic, Subham Choudhury, Ilias Toumpe

Researchers have invested much effort into developing kinetic models due to their ability to capture dynamic behaviors, transient states, and regulatory mechanisms of metabolism, providing a detailed and realistic representation of cellular processes. Hist ...

AMER CHEMICAL SOC2025

Transfer learning and augmented data-driven parameter prediction for robotic welding

Sichao Liu

Robotic welding envisioned for the future of factories will promote high-demanding and customised tasks with overall higher productivity and quality. Within the context, robotic welding parameter prediction is essential for maintaining high standards of qu ...

PERGAMON-ELSEVIER SCIENCE LTD2025

An Exponentially Converging Particle Method for the Mixed Nash Equilibrium of Continuous Games

Lénaïc Chizat, Guillaume Yitian Wang

We consider the problem of computing mixed Nash equilibria of two-player zero-sum games with continuous sets of pure strategies and with first-order access to the payoff function. This problem arises for example in game-theory-inspired machine learning app ...

2025

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

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

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

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

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

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

Investigating neural resource allocation in the sensorimotor control of extra limbs

Giulia Dominijanni

The rise of robotic body augmentation brings forth new developments that will transform robotics, human-machine interaction, and wearable electronics. Extra robotic limbs, although building upon restorative technologies, bring their own set of challenges i ...

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

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

Gas Sensing with Rotary-Wing Nano Aerial Vehicles

Chiara Ercolani

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 ...

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

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Alireza Modirshanechi

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

EPFL2024

Toward more naturalistic tactile sensors

Silvestro Micera

The human hand is a remarkable organ used every day to interact with the world. To achieve this, the hand is equipped with several sophisticated natural sensors that perceive touch, position, and temperature. Artificial systems that mimic the natural sense ...

American Association for the Advancement of Science2024

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

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

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

MapPool -Bubbling up an extremely large corpus of maps for AI

Raimund Thies Schnürer

MapPool is a dataset of 75 million potential maps and textual captions. It has been derived from CommonPool, a dataset consisting of 12 billion text-image pairs from the Internet. The images have been encoded by a vision transformer and classified into map ...

2024