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Perceiving the person and their interactions with the others for social robotics - A review

机译:感知人及其与他人的互动以进行社交机器人学-综述

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Social robots need to understand human activities, dynamics, and the intentions behind their behaviors. Most of the time, this implies the modeling of the whole scene. The recognition of the activities and intentions of a person are inferred from the perception of the individual, but also from their interactions with the rest of the environment (i.e., objects and/or people). Centering on the social nature of the person, robots need to understand human social cues, which include verbal but also nonverbal behavioral signals such as actions, gestures, body postures, facial emotions, and proxemics. The correct understanding of these signals helps these robots to anticipate the needs and expectations of people. It also avoids abrupt changes on the human-robot interaction, as the temporal dynamics of interactions are anchored and driven by a major repertoire of social landmarks. Within the general framework of interaction of robots with their human counterparts, this paper reviews recent approaches for recognizing human activities, but also for perceiving social signals emanated from a person or a group of people during an interaction. The perception of visual and/or audio signals allow them to correctly localize themselves with respect to humans from the environment while also navigating and/or interacting with a person or a group of people. (C) 2018 Elsevier B.V. All rights reserved.
机译:社交机器人需要了解人类的活动,动态及其行为背后的意图。大多数情况下,这意味着对整个场景进行建模。对一个人的活动和意图的认识是从对个人的感知中推断出来的,但也从他们与环境的其余部分(即物体和/或人)的相互作用中推断出来的。围绕人的社会本质,机器人需要了解人类的社会暗示,包括言语但非言语的行为信号,例如动作,手势,身体姿势,面部表情和近距离感。对这些信号的正确理解有助于这些机器人预测人们的需求和期望。它也避免了人机交互的突然变化,因为交互的时间动态是由主要的社会地标组成的,并由它们驱动。在机器人与人类人类交互的一般框架下,本文回顾了识别人类活动的最新方法,以及在交互过程中感知一个人或一群人发出的社会信号的方法。视觉和/或音频信号的感知使他们能够从环境中正确地相对于人类定位自己,同时还可以与一个人或一群人进行导航和/或交互。 (C)2018 Elsevier B.V.保留所有权利。

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