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Aiming at the problem of underwater glider path planning, an underwater glider path planning method based on Q-Learning is proposed. Considering that the Underwater Glider will give the pitch angle and depth parameters in advance when performing some specific tasks, and the course angle selection range is usually several discrete angle values, this paper designs the course action selection sets for several typical pitch angles under the condition of certain depth, which avoids the problem of "dimension explosion" of Q-learning method. According to the shortest path target of underwater glider and the external constraints of obstacles, the reward function and action selection strategy are designed. Compared with the traditional path planning methods, the proposed method does not need to know the environmental information in advance, but selects the optimal action according to the feedback of the environment in the learning process. Therefore, this method has excellent migration ability under different environmental conditions. Simulation results show that this method can plan an obstacle avoidance and short range path for underwater glider in unknown environment.