Emotional Behavior Decision Method and Its Experiments of Generality for Applying to Various Social Robot Systems

목적과 사양이 다른 다양한 인간 친화 로봇에 적용하기 위한 감성 행동 생성 방법 및 범용성 실험

  • 안호석 (한국생산기술연구원 로봇융합연구그룹) ;
  • 최진영 (서울대학교 전기컴퓨터공학부) ;
  • 이동욱 (한국생산기술연구원 로봇융합연구그룹)
  • Received : 2011.04.22
  • Accepted : 2011.07.06
  • Published : 2011.07.25

Abstract

Emotional reaction should be different from the purpose of the robot system. The method for emotional reaction is also different from the specification of the robot system. Therefore, emotional behavior decision model, which is applied to social robots regardless of specifications and purposes, is necessary. This paper introduces a universal emotional behavior decision model designed for applying to various social robots that have different specifications and purposes. Multiple emotions, a set of probability value of every emotion, are calculated independently and expressed according to the purpose of the robot system. Then, behavior, for emotional reaction according to the calculated multiple emotions, is decided regarding the specification of the robot system. The decided behavior is a combination of unit behaviors that indicates the smallest expressible behaviors in each expression parts. It is possible to express various undefined behaviors by generating unit behavior combinations according to multiple emotions. The universal emotional behavior decision model is applied to three kinds of social robot systems that have different specifications and purposes.

감성 행동을 표현하는 것은 인간 친화 로봇의 필수 요소 중 하나이다. 하지만 감성 행동은 로봇의 목적이나 사양에 따라서 달라지기 때문에 감성 행동을 생성하고 표현하는 방법은 로봇마다 다르다. 따라서 본 논문에서는 로봇의 목적이나 사양에 상관없이 다양한 인간 친화 로봇에 적용될 수 있는 감성 행동 생성 방법을 제안한다. 먼저 감성 행동 생성 방법의 입력 값으로 다중 감정값을 이용한다. 다중 감정 공간을 이용하여 각 감정이 독립적으로 존재할 수 있기 때문에 로봇의 목적에 따라 사용하고자 하는 감정을 취사선택할 수 있다. 로봇의 사양에 따라서 표현할 수 있는 방법이 다르므로, 로봇의 표현 부위를 나누고, 각 표현 부위별로 표현할 수 있는 행동을 데이터화한다. 이렇게 나누어진 행동들을 단위 행동이라고 정의하며, 각 단위 행동이 표현할 수 있는 감정에 대한 반영도를 결정한다. 그리고 이를 이용하여 주어진 다중 감정값에 최적화된 단위 행동 조합을 결정한다. 이 과정을 사양과 목적이 다른 사이버 로봇 시뮬레이터, 3D 캐릭터 헤드 로봇, 기계적인 설계 기반의 헤드 로봇 등에 적용함으로써 제안한 방법의 범용성을 실험한다.

Keywords

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