Hand-Object Interaction: From Human Demonstrations to Robot Manipulation

被引:7
|
作者
Carfi, Alessandro [1 ]
Patten, Timothy [2 ]
Kuang, Yingyi [3 ]
Hammoud, Ali [4 ]
Alameh, Mohamad [1 ]
Maiettini, Elisa [5 ]
Weinberg, Abraham Itzhak [3 ]
Faria, Diego [3 ]
Mastrogiovanni, Fulvio [1 ]
Alenya, Guillem [6 ]
Natale, Lorenzo [5 ]
Perdereau, Veronique [4 ]
Vincze, Markus [2 ]
Billard, Aude [1 ,7 ]
机构
[1] Univ Genoa, Dept Informat Bioengn Robot & Syst, Genoa, Italy
[2] Tech Univ Wien, Inst Automatisierungs & Regelungstechnik, Vis Robot Lab, Vienna, Austria
[3] Aston Univ, Coll Engn & Phys Sci, Robot Vis & Intelligent Syst, Birmingham, W Midlands, England
[4] Sorbonne Univ, Inst Systemes Intelligents & Robot, Paris, France
[5] Ist Italiano Tecnol, Humanoid Sensing & Percept, Genoa, Italy
[6] CSIC UPC, Inst Robot Informat Ind, Barcelona, Spain
[7] Ecole Polytechn Federale Lausanne, Learning Algorithms & Syst Lab, Lausanne, Switzerland
来源
基金
英国工程与自然科学研究理事会; 奥地利科学基金会;
关键词
hand-object interaction; learning from demonstration; imitation learning; transfer learning; grasping; manipulation; anthropomorphic hands; data extraction; TEMPORAL SEGMENTATION; IMITATION; TASKS;
D O I
10.3389/frobt.2021.714023
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
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.
引用
收藏
页数:7
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