Obstacle recognition and path planning are the necessary means for robot to move autonomously. Based on depth camera, this paper proposes an obstacle recognition method based on the fusion of depth continuity and color feature points. The spatial location information of objects is obtained by depth camera and mapped to the existing map to construct the obstacle space. A path planning method of PRM-D∗ is proposed. Firstly, the improved random probability roadmap ( PRM) is used to complete the overall path planning. Then, according to the obstacles identified by the camera, the local map is set up, and the D∗ algorithm based on graph search is used to carry out local dynamic planning to complete the dynamic obstacle avoidance task. Through the experiment, the detection accuracy of the proposed obstacle recognition method is greater than 80% even in dim indoor environment, and the accuracy of conventional environmental detection is higher than 95%, and it has good robustness and real-time performance; The path planning method of PRM-D∗ not only shortens the overall planning time, but also ensures the success rate of path planning. The single dynamic planning time is less than 0. 02 s, and has good dynamic obstacle avoidance performance.