Developing a Virtual Knowledge Map Navigation for Contest-based Robot

• Main Authors: Shuen-ren Yu, 尤舜仁
• Other Authors: Chao-chi Chan
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/94301052017335534410

博士 === 國立臺灣科技大學 === 機械工程系 === 100 === 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.