Publications associées à Modulation of motor primitives using force feedback: Interaction with the environment and bimanual tasks

Publications associées (33)

Robot Learning using Tensor Networks

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

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

Geometric and Learning Methods for Robots to Navigate in Human Crowds with Application to Smart Mobility Devices

David Julian Gonon

The thesis at hand is concerned with robots' navigation in human crowds. Specifically, methods are developed for planning a mobile robot's local motion between pedestrians, and they are evaluated in experiments where a robot interacts with real pedestrians ...

EPFL2023

Human Interactive Robotic Surfaces for Physical Immersion

Fabio Zuliani

Computers have long been augmenting human capabilities and communication, and with emerging technologies, physical immersion in virtual worlds is now attainable. These advancements push the boundaries of human potential, allowing designers, architects, eng ...

EPFL2023

Human-Robot Swarm Interaction: An Explorative Path to Foster Complex Systems Understanding

Hala Khodr

Order, regularities, and patterns are ubiquitous around us. A flock of birds maneuvering in the sky, the self-organization of social insects, a global pandemic or a traffic jam are examples of complex systems where the macroscopic patterns arise from the m ...

EPFL2023

A geometric optimal control approach for imitation and generalization of manipulation skills

Sylvain Calinon, Amirreza Razmjoo Fard

Daily manipulation tasks are characterized by regular features associated with the task structure, which can be described by multiple geometric primitives related to actions and object shapes. Only using Cartesian coordinate systems cannot fully represent ...

Elsevier2023

Learning and optimization of anticipatory feedback controllers for robot manipulation

Hakan Girgin

Programming intelligent robots requires robust controllers that can achieve desired tasks while adapting to the changes in the task and the environment. In this thesis, we address the challenges in designing such adaptive and anticipatory feedback controll ...

EPFL2023

Prescribing Cartesian Stiffness of Soft Robots by Co-Optimization of Shape and Segment-Level Stiffness

Josephine Anna Eleanor Hughes, Francesco Stella

Soft robots aim to revolutionize how robotic systems interact with the environment thanks to their inherent compliance. Some of these systems are even able to modulate their physical softness. However, simply equipping a robot with softness will not genera ...

MARY ANN LIEBERT, INC2023

A biohybrid interaction framework for the integration of robots in animal societies

Francesco Mondada, Vaios Papaspyros, Daniel Burnier, Raphael Cherfan

The collective behavior of animals has been traditionally studied through observation, quantitative models of behavior, and devices of low intelligence. Nowadays, the advancements in the field of robotics allow for closed-loop experiments that occur in rea ...

2023

Scattering from Time-Modulated Transmission-Line Loads: Theory and Experiments in Acoustics

Romain Christophe Rémy Fleury, Matthieu Francis Malléjac

Scattering wave systems that are periodically modulated in time offer many new degrees of freedom to control waves in both the spatial and frequency domains. Such systems, albeit linear, do not conserve frequency and require the adaptation of the usual the ...

American Physical Society (APS)2023

Haptics based collaborative steering control in automated driving environments

Tomohiro Nakade

A vehicle's steering is a particular system in that it is exposed to individual subjective reviews based on criteria that are hard to assess quantitatively. Haptic design of such systems is a prime concern that has been at the center of industrial developm ...

EPFL2023

Programmable Silicon Nitride Photonic Integrated Circuits

Tobias Kippenberg, Johann Emmeram Riemensberger, Rui Ning Wang, Anat Siddharth, Andrey Voloshin, Viacheslav Snigirev, Andrea Bancora, Vladimir Shadymov

Silicon Nitride (Si3N4) photonic integrated circuits (PICs) have emerged as core technology in a variety of applications ranging from LIDAR to quantum control and computing. However, the need for high-speed, low-voltage tuning and modulation has been a lon ...

IEEE2023

Improving hand prosthesis control with advanced single-finger proportional decoding and robotic shared control

Vincent Alexandre Mendez

Myoelectric prostheses allow users to recover lost functionality by controlling a robotic device with their remaining muscle activity. Commercial devices usually use a two-recording-channel system placed on specific muscles to control a single degree of fr ...

EPFL2023

Reticular chemistry for the rational design of mechanically robust mesoporous merged-net metal-organic frameworks

Berend Smit, Seyedmohamad Moosavi

Access to metal-organic frameworks (MOFs) with enhanced me-chanical stability is key to their successful deployment in practical applications. However, the high porosity of the material often af-fects mechanical stability. In this article, to achieve highl ...

CELL PRESS2023

Identifying important sensory feedback for learning locomotion skills

Auke Ijspeert, Guillaume Denis Antoine Bellegarda, Milad Shafiee Ashtiani

Robot motor skills can be acquired by deep reinforcement learning as neural networks to reflect state-action mapping. The selection of states has been demonstrated to be crucial for successful robot motor learning. However, because of the complexity of neu ...

NATURE PORTFOLIO2023

Exploration-based model learning with self-attention for risk-sensitive robot control

Sudong Lee

Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for policy improvement in model-free methods. However, both methods use exploration strategy relying on heuristics ...

2023

Device and system as human interactive surface

Jamie Paik, Fabio Zuliani

A force-feedback surface that creates and modulates distinctive profile and stiffnessto interact with a user in contact thereto, the surface being functionally independentto be used as a single module but can be customized to extend the application indiver ...

2023

Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid

John Martin Kolinski, Lebohang Molefe

Surface stress drives long-range elastocapillary interactions at the surface of compliant solids, where it has been observed to mediate interparticle interactions and to alter the transport of liquid drops. We show that such an elastocapillary interaction ...

2023

Liquid Metal-Based Sensor Skin Enabling Haptic Perception of Softness

Stéphanie Lacour, Ivan Furfaro, Haotian Chen, Emilio Fernández Lavado

Haptic perception of softness is a unique feature of the human skin that relies on the concurrent measurements of the lateral deformation and compression of the skin during object manipulation. This is challenging to implement in robotics because of combin ...

2023

A theory of memory consolidation and synaptic pruning in cortical circuits

Georgios Iatropoulos

Over the course of a lifetime, the human brain acquires an astonishing amount of semantic knowledge and autobiographical memories, often with an imprinting strong enough to allow detailed information to be recalled many years after the initial learning exp ...

EPFL2023