To address the issues of path redundancy and low coverage in intelligent cleaning robot path planning, a hybrid algorithm for full coverage path planning is proposed, which integrates the semi-spring artificial potential field method, A* algorithm, and dynamic update strategy. This aims to solve the problem effectively. The A* algorithm is used for initial path planning, while the semi-spring artificial potential field method is employed for local obstacle avoidance to reduce local optima issues. The dynamic coverage value update strategy optimizes path priority based on real-time coverage, improving coverage efficiency and reducing redundant coverage. Additionally, the dynamic weight adjustment mechanism based on fuzzy logic enables the algorithm to adaptively adjust coverage and obstacle avoidance weights in complex environments. Simulation results indicate that the hybrid algorithm achieves higher coverage rates and lower redundant coverage compared to other algorithms. This has been further validated through real-world vehicle tests, demonstrating its capability to meet the full coverage operation requirements of cleaning robots.