A stream algorithm is proposed to address the low search efficiency of traditional algorithms in mobile robot path planning. Firstly, the algorithm obtains all the main points through the main point search model. Flow step by step from the starting point, when a single obstacle is encountered, the stream obstacle avoidance algorithm is invoked to avoid the obstacle. When multiple obstacles are encountered, the pseudo-virus algorithm is called to mark these obstacles. Then, the stream obstacle avoidance algorithm is called to avoid obstacles until the end. Finally, the resulting path is smooth. A variety of map environments are modeled by using the grid method. The path length and running time of the stream algorithm are compared with those of the ant colony algorithm, Dijkstra algorithm, and Floyd algorithm in simulation studies. The testing results show that, compared with the A ∗ algorithm which achieves the shortest path and the least time, the average path length obtained by the stream algorithm is reduced by 2. 40% ~ 6. 30% , and the average time is reduced by 35. 71% ~ 53. 51% . To test the application of the stream algorithm in the actual scene, it is applied to the mobile robot Turtlebot2 and conducted a comparative experiment with the A ∗ algorithm. The experimental results show that, compared with the A ∗ algorithm, the measured path is increased by 3. 83% , the running time is reduced by 10. 77% , and the number of inflection points is reduced by 42. 86% .