Extremely sensitive odor sensors are required for odor searching in mobile robots. The male silkmoth (Bombyx mori) is a candidate biosensor because of its high sensitivity to the conspecific sex pheromone with stereotypic searching behavior. Furthermore, the odor preferences of silkmoths can be modified using genetic tools. Therefore, techniques that can easily detect the odor response of silkmoths with high sensitivity have become important for odor detection and searching. In recent years, machine learning has been used to classify the behaviors of silkmoths to estimate the timing of odor reception. Therefore, it is possible to utilize a silkmoth’s behavioral response as an olfactory sensor for robotic odor searching. In this work, we developed an odor- searching mobile robot with an odor sensing device based on a silkmoth’s walking pattern. First, we collected behavioral data with and without odor stimuli. Then, we predicted the presence of an odor using a support vector machine. Finally, we implemented the sensing device in an odor- searching robot and demonstrated that the classifier performance was sufficient for a robot to localize an odor source by utilizing artificial searching algorithms. These results indicated the feasibility of an insect-behavior-based olfactory sensor for robotic odor searching.