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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/71931


    Title: 應用於情感機器人長期互動之情緒、心情與態度六一情感模型;SO-EMA: A Six-One Emotion, Mood and Attitude Affective Model for Long-term Interaction
    Authors: 劉哲延;Liu,Che-Yen
    Contributors: 通訊工程學系
    Keywords: 情感機器人
    Date: 2016-07-11
    Issue Date: 2016-10-13 14:07:13 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 本論文建立情感機器人長期互動之情緒、心情與態度六一情感模型(A Six-One Emotion, Mood and Attitude Affective Model for Long-term Interaction, SO-EMA),以量化的方式來表達機器人的各種情緒,並建立一套情感與表情的相對應關係,隨著外部事件刺激與內部情緒之轉變,以及針對不同對象的互動差異性,進一步設計出機器人長期互動的情感演算法。

    在SO-EMA演算法中,隨著時間及不同對象的事件演進,機器人藉由接收不同對象產生的事件刺激,經由可調整的機器人的人格以及與對象的「態度」權重計算產生量化的情感反應,與當下的情緒與心情合成為下一刻的情緒與心情,在這樣情感狀態轉變過程中,機器人對於每個對象都有不同情緒的「態度」,因為互動時間與情感起伏來週期產生下一次的態度,所以經由長期的互動下,機器人與每個對象的態度都會有所差異,更能表達出人類真實在群體中的情感表現。

    最後,用實驗結果來證明SO-EMA在長期與人類互動符合人類的情感表現,因此,SO-EMA演算法的建立使得機器人與人類的互動更自然、類似人類的情緒反應且發展更加全面。
    ;In this thesis, we build a social affective robot by quantizing robot’s every kind of Emotion and building a corresponding relation of affection and expression. Affection includes Emotion, Mood and Attitude. Along with the transition of internal and external stimulus and the interactive difference regarding to different objects, we design the affection algorithm (SO-EMA) of long-term interaction and behavior improvement.

    In SO-EMA, with time and different objects’ even evaluating, robots receive stimulus even by different objects, calculate the weight of quantifiable Affection responds by adjustable personality and Attitude, and combine the present affection to generate the next state of affection. In the process of Affection transition, robot keeps different Attitude to different objects. The next state of Attitude will be generated by interaction time and Affection fluctuating periodically. Thus, in long-term interaction, we can see the differences on the Attitude between different objects and the true affective expression of human in group.

    In the end of this thesis, we propose several experimental data to prove that SO-EMA meet the affection expression of interaction, and improve the relationship between human in long-term.
    Appears in Collections:[通訊工程研究所] 博碩士論文

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