This paper focuses on the path planning for a mobile robot which is operated in indoor environment. Since the layout of indoor environment is a hybrid structure of known and unknown, this paper presents a hybrid algorithm which uses the Max-Q method and the option method together. Firstly, a novel task graph and high level definition are presented to divide sub-tasks. Then, the appropriate definitions of states, actions and options could let a robot fulfill a task. Finally, an angle parameter is employed in the reward function to ensure a robot select a shorter path and adjust orientation timely. In the series of simulations, a robot can arrival any position successfully with random initial positions and directions. Moreover the results show that a robot can overcome the local minimal problem with our hybrid method.