Path planning is one of the most important fields in robotics. Only a limited number of articles have proposed a practical way to solve the path-planning problem with moving obstacles. In this paper, a fuzzy path-planning method with two strategies is proposed to navigate a robot among unknown moving obstacles in complex environments. The static form of the environment is assumed to be known, but there is no prior knowledge about the dynamic obstacles. In this situation, an online and real-time approach is essential for avoiding collision. Also, the approach should be efficient in natural complex environments such as blood vessels. To examine the efficiency of the proposed algorithm, a drug delivery nanorobot moving in a complex environment (blood vessels) is supposed. The Monte Carlo simulation with random numbers is used to demonstrate the efficiency of the proposed approach, where the dynamic obstacles are assumed to appear in exponentially distributed random time intervals.