Robots for Learning - R4L: Adaptive Learning

Publications associées (31)

À propos
Confidentialité
Mentions légales

Graph Chatbot

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

Teacher's Perception on Social Robots to Promote the Integration of Children with Migration Background

Arzu Güneysu Özgür, Daniel Carnieto Tozadore

This paper describes the first steps of an ongoing participatory design with teachers from Switzerland to co-create Human-Robot Interaction setups for integrating children with migration history. The herein presented phase had two main goals: (i) initially ...

Association for Computing Machinery2023

Language Learning using Caption Generation within Reciprocal Multi-Party Child-Tutor-Tutee Interaction

Barbara Bruno

Reciprocal Peer Tutoring (RPT) is a learning paradigm characteristic of collaborative interaction between learners with alternating tutortutee roles. In recent years, robot-assisted language learning (RALL) has gained traction by its wide application for l ...

ASSOC COMPUTING MACHINERY2023

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

Immediate effects of short-duration wellbeing practices on children’s handwriting and posture guided by a social robot

Pierre Dillenbourg, Chenyang Wang, Barbara Bruno, Daniel Carnieto Tozadore, Melike Cezayirlioglu

Handwriting practising, as any other repetitive task, often leads the practiser to an overconcentration state where their performance might be affected by postural and mental fatigue. Short breaks to perform unrelated activities, especially relaxation exer ...

2023

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

Liquid Metal-Based Sensor Skin Enabling Haptic Perception of Softness

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

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

Implicit Distance Functions: Learning and Applications in Robotics

Mikhail Koptev

In this thesis, we address the complex issue of collision avoidance in the joint space of robots. Avoiding collisions with both the robot's own body parts and obstacles in the environment is a critical constraint in motion planning and is crucial for ensur ...

EPFL2023

The science of soft robot design: A review of motivations, methods and enabling technologies

Josephine Anna Eleanor Hughes, Francesco Stella

Novel technologies, fabrication methods, controllers and computational methods are rapidly advancing the capabilities of soft robotics. This is creating the need for design techniques and methodologies that are suited for the multi-disciplinary nature of s ...

FRONTIERS MEDIA SA2023

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

Page 3 sur 4