The purpose of this research is to develop a mobile robot which detects wood splinters automatically. It is hard to find the wood splinters from the floor images because the size of the wood splinters is small and the color is similar. In this research, we develop a mobile robot equipped with two rollers to attach cotton to the wood splinters and object detection to find the location of the wood splinters using the attached cotton. We also build a system to generate a route from a range selected by the inspector and to show results based on running records and detection results. As a result, the accuracy attaching cotton to the wood splinters was 76%. As the precision detecting cotton, the true positive rate was 99%, but there was false positive in the detected result. From the above, we could detect 75% wood splinters. As the result of the running test through the gymnasium, the total inspection time was 87 minutes, and the operation took one person when setting and no person when running, and inspection omission was at most 2.4%. By increasing the number of the dataset of the floor image including the cotton, we will improve this accuracy and reduce false positive when detecting cotton from now.