A Study on Quantitative Evaluation Methods for Measurement of Disaster Response Robot Operator Proficiency, and Verification of Training Effectiveness using ANOVA

Recently, as social infrastructure has become more complex, disasters have become large-scale and difficult to predict. Responding to disasters using the existing equipment is challenging because of this complexity. In this situation, the demand for robotic technology to reduce human casualties and respond effectively to disasters is gradually increasing. To increase the field usability of disaster response robots, not only the distribution of robots but also the development of appropriate robot training methods should be conducted in parallel. This study proposes a disaster response robot operator training method and quantitatively verifies its effectiveness. To increase the proficiency of trainees, we propose a training method involving sequential beginner, intermediate, and advanced training stages. To quantitatively verify the effectiveness of the training, the experimental group was divided into three groups: control, general test, and MR test, and the results were confirmed through ANOVA.