Publications related to Customizing skills for assistive robotic manipulators, an inverse reinforcement learning approach with error-related potentials

Related publications (14)

Report A sensory-motor hand prosthesis with integrated thermal feedback

Silvestro Micera, Solaiman Shokur, Outman Akouissi, Jonathan Louis Muheim

Background: Recently, we reported the presence of phantom thermal sensations in amputees: thermal stimulation of specific spots on the residual arm elicited thermal sensations in their missing hands. Here, we exploit phantom thermal sensations via a standa ...

Cell Press2024

Modeling and experimental study of a miniaturized magnetorheological valve with high performance

Yves Perriard, Christian Köchli, Sofia Lydia Ntella

Magnetorheological (MR) valves attracted the interest of researchers across diverse fields, owing to the controllable nature of MR fluid. The use of MR fluid in valves enables fast response, energy efficiency, and robustness, while several studies designed ...

Sage Publications Ltd2024

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

Heading for the Abyss: Control Strategies for Exploiting Swinging of a Descending Tethered Aerial Robot

Josephine Anna Eleanor Hughes, Max Mirko Polzin

The use of aerial vehicles for exploration and data collection has the potential to significantly aid environmental monitoring in environments which are dangerous and hard to navigate. However, within these environments navigation can often be restricted b ...

2023

Demonstration-guided Optimal Control for Long-term Non-prehensile Planar Manipulation

Sylvain Calinon, Teng Xue

Long-term non-prehensile planar manipulation is a challenging task for robot planning and feedback control. It is characterized by underactuation, hybrid control, and contact uncertainty. One main difficulty is to determine both the continuous and discrete ...

IEEE2023

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

Silvestro Micera, Simone Romeni

Objective. Peripheral nerve interfaces have the potential to restore sensory, motor, and visceral functions. In particular, intraneural interfaces allow targeting deep neural structures with high selectivity, even if their performance strongly depends upon ...

IOP Publishing Ltd2023

How Rough Is the Path? Terrain Traversability Estimation for Local and Global Path Planning

Tobias Löw

Perception and interpretation of the terrain is essential for robot navigation, particularly in off-road areas, where terrain characteristics can be highly variable. When planning a path, features such as the terrain gradient and roughness should be consid ...

IEEE Institute of Electrical and Electronics Engineers2022

EMG-driven shared human-robot compliant control for in-hand object manipulation in hand prostheses

Aude Billard, Silvestro Micera, Iason Batzianoulis, Vincent Alexandre Mendez, Farshad Khadivar, Carolina Gaspar Pinto Ramos Correia

Objective. The limited functionality of hand prostheses remains one of the main reasons behind the lack of its wide adoption by amputees. Indeed, while commercial prostheses can perform a reasonable number of grasps, they are often inadequate for manipulat ...

IOP Publishing Ltd2022

Low-Level Physiological Implications of End-to-End Learning of Speech Recognition

Philip Neil Garner

Current speech recognition architectures perform very well from the point of view of machine learning, hence user interaction. This suggests that they are emulating the human biological system well. We investigate whether the inference can be inverted to p ...

ISCA-INT SPEECH COMMUNICATION ASSOC2022

Investigation of effective processes parameters on lead (II) adsorption from wastewater by biochar in mild air oxidation pyrolysis process

Farzaneh Talebkeikhah, Mohsen Talebkeikhah

This study evaluates and compares several machine learning methods on the effects of different parameters in lead adsorption capacity. pH, contact time, adsorbent dosage and initial lead concentration were considered as inputs and adsorption capacity was r ...

TAYLOR & FRANCIS LTD2022

Postural Control and Consciousness and Their Applications to Lower-Limb Exoskeletons

Jemina Fasola

Human postural control requires high coordination and is distributed over the whole musculoskeletal and nervous systems. Hence, postural balance can be impaired due to various pathologies. Efficient rehabilitation programs and technological solutions are t ...

EPFL2020

Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning

Alexandre Massoud Alahi, Sven Kreiss, Yuejiang Liu

Mobility in an effective and socially-compliant manner is an essential yet challenging task for robots operating in crowded spaces. Recent works have shown the power of deep reinforcement learning techniques to learn socially cooperative policies. However, ...

IEEE2019

Bi-Modal Control of Vacuum-Powered Soft Pneumatic Actuators with Embedded Liquid Metal-Based Strain Sensitive Skin

Stéphanie Lacour, Jamie Paik, Matthew Aaron Robertson, Laurent Mirko Dejace

Soft robotic systems are composed of active and passively deformable structures which are intrinsically compliant, flexible, and elastic. Although these features offer benefits of adaptability, robustness, and safety, controlling these types of robots is a ...

IEEE2019

Reverse engineering the motor control system

Berat Denizdurduran

Mammalian motor control is implemented by a combination of different networks and system, working coherently to plan the movement of the body or a limb and to execute this movement a dynamical environment. While it is believed that complex, voluntary movem ...

EPFL2019