We are conducting research to instill XR (VR / AR / MR), UX / UI, and sustainable (SDGs) that lead to next-generation technologies into the real world. These combine a wide range of design engineering, ergonomics, electrical and electronic engineering, and mechanical engineering to create something useful to humans. Throughout your research life, you will acquire the technology to integrate image processing, mechatronics, 3D-CAD, sensing, and machine learning. Let's challenge boldly without fear of failure.
Faculty name/Affiliation | Iku Mihashi / Department of Mechanical and Precision Systems Faculty of Science and Engineering |
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Specialized Fields | User experience, design engineering, augmented reality, ergonomics, educational technology |
Research theme |
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Research keywords | User Experience (UX), Man Machine User Interface (UI), Virtual Reality (VR), Augmented Reality (AR), 3D-CAD, Ergonomics, Motion Capture, Sensing Engineering, Robotics, Machine Learning |
Faculty introduction URL | https://www3.med.teikyo-u.ac.jp/profile/ja.8e2ed0215aa57ef4.html |
Skill movements in vocational training often require equipment, time, and manpower because they are often trained by memorizing the movements of skilled workers by imitating them. As one of the methods to solve this, there is a simulation using a flight simulator with high reproducibility, but the training effect is unknown because it is necessary to prepare dedicated equipment and because the reality is too important. is. Therefore, in this research, we will focus on entertainment by adding points to the competition, and build a motion training game with multiple viewpoint functions that is impossible in reality. Currently, we are proposing games for centering lathes, paralleling milling machines, and arc welding work, and evaluating the effectiveness of motion training games by comparing actual vocational training movements.
When communicating the movements of an expert to a beginner, it is difficult to convey them with words and gestures alone, and it is difficult to quantitatively evaluate excellent skills. In this research, the behavioral trajectory of multiple joints is curved (behavioral curved surface) to clarify the difference in behavior between experts and beginners. The behavior curved surface is evaluated by the curved surface shape, curvature, area, etc., and the curvature is expressed by color gradation so that it can be visually understood. Furthermore, in order to visualize the rhythm and timing of movement, we create a behavior curve with speed, acceleration, and propulsion force information added in color gradation as well as the trajectory, and evaluate the behavior of the expert.
Robot creation education requires three skills of mechanism, electronic circuit, and program, but even in university education, it is difficult to achieve all three at the same time, especially motor control by programming is extremely difficult, easy and diverse. If motor control is possible, robot education will become more widespread. Therefore, in this research, we propose a motor control method that anyone can operate, a simple housing and mechanism, and a modular robot education system to co-create and extract experience value of each learner. I am.