基于Laban运动分析的人形机器人平台字符识别

A. Bacula, A. LaViers
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引用次数: 7

摘要

一个活跃的研究领域是探索如何在机器人平台上模仿人类的运动。实现这一目标的一步是能够创造一种方法,使机器人平台成功地描绘出人类可以识别的角色或角色特征。芭蕾舞是一种通过动作来传达可识别的人物类型的表演艺术。本文基于上半身动作,探讨了古典芭蕾中原型人物的识别和区分,并将此信息应用于机器人平台。使用拉班动作分析(LMA)创建了一个观察指南,用于分析几个经典芭蕾舞剧中不同角色的动作。我们选择了11个例子:3个反派角色类型,3个小鸟角色类型和5个垂死角色类型。利用观察指南跟踪这些角色的上半身运动,看看他们的运动是否以可区分的方式利用了LMA特征。跟踪运动的结果进行了分析,并在NAO机器人上创建了运动序列,以模拟这些字符类型:随后通过用户研究验证的过程。
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Character Recognition on a Humanoid Robotic Platform via a Laban Movement Analysis
An active area of research is exploring how to mimic human movement on a robotic platform. One step toward achieving this goal is the ability to create a method in which a robotic platform successfully portrays a character or character traits that a human can recognize. Ballet is a performing art in which recognizable character types are conveyed through movement. This paper explores the recognition and differentiation of archetypal characters used in classical ballet based on their upper body movements and applies this information to a robotic platform. An observational guide was created using Laban Movement Analysis (LMA) for analyzing the movements of distinct characters found across several classical ballets. Eleven examples were chosen: three villain character types, three bird character types, and five dying character types. The upper body movements of these characters were tracked utilizing the observational guide to see if their movements utilized the LMA characteristics in distinguishable ways. The results from tracking the movements were analyzed, and movement sequences were created on a NAO robot to emulate these character types: a process subsequently validated by a user study.
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