To realize efficient path exploration of unmanned platforms in unknown environments, a path planning algorithm based on a hierarchical architecture of “perception planning control” is studied in this work. Real-time construction of two-dimensional grid maps of unknown environments using the Cartographer mapping algorithm at the perception layer. At the planning level, the optimal exploration target point is selected by Canny edge detection, density-based clustering algorithm, and performance function evaluation. Specifically, the concept of continuity of exploration direction is introduced into the efficiency function of planning, overcoming the drawbacks of traditional path planning that repeatedly explores known environments. At the control layer, the shortest path from the current pose to the target point is planned using probability roadmap algorithm, and collision-free tracking of the path is achieved through pure tracking algorithm and vector histogram algorithm. The effectiveness of the algorithm was verified through simulation in three typical environments, and the results showed that the proposed algorithm can achieve higher exploration efficiency and completeness in different environments.