Insects perform adaptive behavior according to changing environmental conditions using comparatively small brains. Because adaptability is generated through the relationship among brain, body and environment, it is necessary to examine how a brain works under these conditions. In this study, to understand neural processing involved in adaptive behavior, we constructed a brain?machine hybrid system using motor signals related to the steering behavior of the male silkworm moth for controlling a two-wheeled mobile robot. We developed this hybrid system according to the following steps. (1) We selected steering signals corresponding to walking direction that were activated during neck swinging induced by optic flow and pheromone stimuli. (2) To control a robot by neural activity, we implemented a spike-behavior conversion rule such that frequency of the left and right neck motor neurons’ spikes was linearly converted into rotation of the wheels. (3) For electrophysiological multi-unit recordings on a robot, we developed small amplifiers. Using this hybrid system, we could observe the programmed behavioral pattern and orientation toward a pheromone source. Moreover, we compared the orientation behavior of moths and that of the hybrid system at different pheromone stimulus frequencies. From these experiments, we concluded that we could reconstruct silkworm moth behavior on the hybrid system.