由於網際網路的資源媒體愈趨多元化，使得知識組織成為一個極為重要的研究領域。知識導航就是運用多種先進技術，主動地提供知識的路徑及資訊，以快捷有效的方法，滿足使用者對於知識與訊息的需求。本研究是以「競賽型機器人設計知識」為基礎，以知識本體當作知識導航引擎的架構性元件。
本研究知識本體的構想來自社會科學領域人格心理學的特質理論，提出一個特質導向(trait-oriented)的競賽機器人機能本體模型(functional ontology)，且應用萃思(TRIZ)系統演化法則，藉以得知各機能元件目前的技術演化情形，及未來可能再演化的趨勢。
其次，採用系統思維、陰陽五行學說及紮根理論推導出機器人虛擬性格的5×2核心模型，並提出「周易資訊模型」進行機器人虛擬性格的特徵標記及模糊分群，以獲得不同機器人間「同中有異」及「異中有同」的差異關係，提升前述機能本體的導航效應。
本研究所採用的競賽機器人強調由資訊、電機、機械等專業之整合知識來設計，才能解決各種問題和面對突發狀況，故所提出的知識導航方法不僅可適用於競賽型機器人，也可以應用在其他的工程領域。

Information technologies are enriching consistently and dramatically the amount and quality of documents produced and consumed by worldwide knowledge workers. How to retrieve really helpful and accurate information in more effective ways is definitively an urgent and challenging topic for knowledge-intense organizations. Enabling reuse and sharing of diverse creative design documents archived in the existing robot portal becomes our driving force to develop a novel knowledge navigation approach.
This framework study on ontology-based virtual map is targeted on Taiwan Creative Robot Competition. As qualified competition teams, they are requested to make good integration of robot’s athletic ability, dexterity, control mechanisms and operator's witness. A successful Robot design is evaluated by the overall well-controlled coordination to overcome the barriers. Evolution of the competition rules can be observed as simple ones to complex constraints for inspiring the new ideas of the robot works.
In this study, some classification concepts of robots characteristics (virtual characters) are derived from Trait Theory adopted commonly in personality study of academic social science. A trait-oriented 5x2 core model is presented as the foundation of robotics functional ontology to form a virtual map, composed as of knowledge nodes representing robot design works. It has added some TRIZ evolutionary viewpoints for helping robot community users discover the creative ideas in existing robot designs and figure out technology trends in the coming competitions.
Our navigation framework is based on an ancient Chinese Yin-Yan Five-Element model derived from systems thinking philology as well as Zhou-Yi tagging scheme. This study has mixed and put into practices with fuzzy clustering, grounded theory, Analytic Hierarchy Process (AHP) and Zhou-Yi information model. A case study of better–matching algorithm is used to demonstrate some navigation ways in the robotics knowledge map. These examples highlight easily the creative design features to help users capture the “difference among sameness” and “sameness among difference" among robot teams.

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