TY - JOUR
T1 - Hand-Object Interaction
T2 - From Human Demonstrations to Robot Manipulation
AU - Carfì, Alessandro
AU - Patten, Timothy
AU - Kuang, Yingyi
AU - Hammoud, Ali
AU - Alameh, Mohamad
AU - Maiettini, Elisa
AU - Weinberg, Abraham Itzhak
AU - Faria, Diego
AU - Mastrogiovanni, Fulvio
AU - Alenyà, Guillem
AU - Natale, Lorenzo
AU - Perdereau, Véronique
AU - Vincze, Markus
AU - Billard, Aude
N1 - Publisher Copyright:
© Copyright © 2021 Carfì, Patten, Kuang, Hammoud, Alameh, Maiettini, Weinberg, Faria, Mastrogiovanni, Alenyà, Natale, Perdereau, Vincze and Billard.
PY - 2021/10/1
Y1 - 2021/10/1
N2 - Human-object interaction is of great relevance for robots to operate in human environments. However, state-of-the-art robotic hands are far from replicating humans skills. It is, therefore, essential to study how humans use their hands to develop similar robotic capabilities. This article presents a deep dive into hand-object interaction and human demonstrations, highlighting the main challenges in this research area and suggesting desirable future developments. To this extent, the article presents a general definition of the hand-object interaction problem together with a concise review for each of the main subproblems involved, namely: sensing, perception, and learning. Furthermore, the article discusses the interplay between these subproblems and describes how their interaction in learning from demonstration contributes to the success of robot manipulation. In this way, the article provides a broad overview of the interdisciplinary approaches necessary for a robotic system to learn new manipulation skills by observing human behavior in the real world.
AB - Human-object interaction is of great relevance for robots to operate in human environments. However, state-of-the-art robotic hands are far from replicating humans skills. It is, therefore, essential to study how humans use their hands to develop similar robotic capabilities. This article presents a deep dive into hand-object interaction and human demonstrations, highlighting the main challenges in this research area and suggesting desirable future developments. To this extent, the article presents a general definition of the hand-object interaction problem together with a concise review for each of the main subproblems involved, namely: sensing, perception, and learning. Furthermore, the article discusses the interplay between these subproblems and describes how their interaction in learning from demonstration contributes to the success of robot manipulation. In this way, the article provides a broad overview of the interdisciplinary approaches necessary for a robotic system to learn new manipulation skills by observing human behavior in the real world.
KW - anthropomorphic hands
KW - data extraction
KW - grasping
KW - hand-object interaction
KW - imitation learning
KW - learning from demonstration
KW - manipulation
KW - transfer learning
UR - http://www.scopus.com/inward/record.url?scp=85117111648&partnerID=8YFLogxK
U2 - 10.3389/frobt.2021.714023
DO - 10.3389/frobt.2021.714023
M3 - Article
C2 - 34660702
AN - SCOPUS:85117111648
SN - 2296-9144
VL - 8
JO - Frontiers in Robotics and AI
JF - Frontiers in Robotics and AI
M1 - 714023
ER -