首页|New Robotics Findings from National Sun Yat-Sen University Described (A Robotics Experimental Design Method Based on PDCA: A Case Study of Wall-Following Robots )
New Robotics Findings from National Sun Yat-Sen University Described (A Robotics Experimental Design Method Based on PDCA: A Case Study of Wall-Following Robots )
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on robotics have been published. According to news reporting originating from Kaohsiung City, Ta iwan, by NewsRx correspondents, research stated, "There is a lack of research th at proposes a complete and interoperable robotics experimental design method to improve students' learning outcomes. Therefore, this study proposes a student-or iented method based on the plan-do-check-act (PDCA) concept to design robotics e xperiments." Funders for this research include National Science And Technology Council (Nstc) of The Republic of China. The news correspondents obtained a quote from the research from National Sun Yat -Sen University: "The proposed method is based on our teaching experience and mu ltiple practical experiences of allowing students to do hands-on experiments. It consists of eight steps, mainly including experimental goals, experimental acti vities, robot assembly, robot control, in-class evaluation criteria, and after-c lass report requirements. The after-class report requirements designed in the pr oposed method can help students improve their report-writing abilities. A wall-f ollowing robotics experiment designed using the PDCA method is proposed, and som e students' learning outcomes and after-class reports in this experiment are pre sented to illustrate the effectiveness of the proposed method. This experiment a lso helps students to understand the fundamental application of multi-sensor fus ion technology in designing an autonomous mobile robot. We can see that the prop osed reference examples allow students to quickly assemble twowheeled mobile ro bots with four different sensors and to design programs to control these assembl ed robots. In addition, the proposed in-class evaluation criteria stimulate stud ents' creativity in assembling different wall-following robots or designing diff erent programs to achieve this experiment. We present the learning outcomes of t hree stages of the wall-following robotics experiment."
National Sun Yat-Sen UniversityKaohsiu ng CityTaiwanAsiaEmerging TechnologiesMachine LearningNano-robotRobo tRobotics
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