Gait measurements such as several-meters walk tests and trainings are carried out to evaluate walking ability during health promotion and preventive long-term care services. It is necessary to track both legs and measure the walking parameters such as stride length can be used for fall-risk assessment across several meters. We have proposed a gait measurement robot (GMR): moving gait measurement system for a long-distance walk tests and evaluating dual-task performance while keeping a constant distance. The GMR estimates its own pose and the position of both legs of the participant. The GMR leads the participant from the start to the goal of the walk test while maintaining a certain distance from the participant. To lead the participant in the human living space, the GMR has to detect the movable passage and determine the translational motion considering the velocity of the participant and obstacle avoidance. In this study, we propose a sensor-based realtime motion control method for the GMR considering the leading participant toward the movable passage and obstacle avoidance using fuzzy set theory in a long-distance walk test. To verify the effectiveness of the proposed method, we carried out the experiments in a corridor.