Action representations in robotics: A taxonomy and systematic classification

Author:

Zech Philipp1ORCID,Renaudo Erwan1,Haller Simon1,Zhang Xiang1,Piater Justus1

Affiliation:

1. Department of Computer Science, University of Innsbruck, Tyrol, Austria

Abstract

Understanding and defining the meaning of “action” is substantial for robotics research. This becomes utterly evident when aiming at equipping autonomous robots with robust manipulation skills for action execution. Unfortunately, to this day we still lack both a clear understanding of the concept of an action and a set of established criteria that ultimately characterize an action. In this survey, we thus first review existing ideas and theories on the notion and meaning of action. Subsequently, we discuss the role of action in robotics and attempt to give a seminal definition of action in accordance with its use in robotics research. Given this definition we then introduce a taxonomy for categorizing action representations in robotics along various dimensions. Finally, we provide a meticulous literature survey on action representations in robotics where we categorize relevant literature along our taxonomy. After discussing the current state of the art we conclude with an outlook towards promising research directions.

Funder

H2020 Leadership in Enabling and Industrial Technologies

Publisher

SAGE Publications

Subject

Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modelling and Simulation,Software

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A hybrid skill parameterisation model combining symbolic and subsymbolic elements for introspective robots;Robotics and Autonomous Systems;2023-03

2. Learning Deep Features for Robotic Inference from Physical Interactions;IEEE Transactions on Cognitive and Developmental Systems;2022

3. Robo Ludens;ACM Transactions on Human-Robot Interaction;2021-12-31

4. Robot Multimodal Object Perception and Recognition: Synthetic Maturation of Sensorimotor Learning in Embodied Systems;IEEE Transactions on Cognitive and Developmental Systems;2021-06

5. Toward next-generation learned robot manipulation;Science Robotics;2021-05-12

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