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Inferring individual evaluation criteria for reaching trajectories with obstacle avoidance from EEG signals

Related publications (39)

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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

Self-Correcting Quadratic Programming-Based Robot Control

Aude Billard, Farshad Khadivar, Konstantinos Chatzilygeroudis

Quadratic Programming (QP)-based controllers allow many robotic systems, such as humanoids, to successfully undertake complex motions and interactions. However, these approaches rely heavily on adequately capturing the underlying model of the environment a ...

2023

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Control design for robotic systems is complex and often requires solving an optimization to follow a trajectory accurately. Online optimization approaches like Model Predictive Control (MPC) have been shown to achieve great tracking performance, but requir ...

2023

Safety Concerns Emerging from Robots Navigating in Crowded Pedestrian Areas

Aude Billard, Diego Felipe Paez Granados, Pericle Salvini

The slogan “robots will pervade our environment” has become a reality. Drones and ground robots are used for commercial purposes while semi-autonomous driving systems are standard accessories to traditional cars. However, while our eyes have been riveted o ...

2021

From High-Level to Low-Level Robot Learning of Complex Tasks: Leveraging Priors, Metrics and Dynamical Systems

Nadia Barbara Figueroa Fernandez

Humans have a remarkable way of learning, adapting and mastering new manipulation tasks. With the current advances in Machine Learning (ML), the promise of having robots with such capabilities seems to be on the cusp of reality. Transferring human-level sk ...

EPFL2019

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

Alexandre Massoud Alahi, Yuejiang Liu, Sven Kreiss, Changan Chen

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

Sprawling posture robots are characterized by upper limb segments protruding horizontally from the body, resulting in lower body height and wider support on the ground. Combined with an actuated segmented spine and tail, such morphology resembles that of s ...

EPFL2018

For a safe and successful daily living assistance, far from the highly controlled environment of a factory, robots should be able to adapt to ever-changing situations. Programming such a robot is a tedious process that requires expert knowledge. An alterna ...

2018

Idiap2018

Agile quadrupedal locomotion in animals and robots is yet to be fully understood, quantified or achieved. An intuitive notion of agility exists, but neither a concise definition nor a common benchmark can be found. Further, it is unclear, what minimal leve ...

EPFL2018