In order to improve the efficiency of crane path planning, a crane path planning algorithm based on improved rapidly-exploring random tree (RRT) is proposed. The generalized distance is used to replace the Euclidean distance in classical RRT, which solves the problem of unclear definition of distance in RRT with multiple degrees of freedom(DOF). Based on the concept of dimensionality reduction, the cell method divides the configuration space (C space) into equal-sized cells, which solves the problem of low efficiency in computing time and resources of the nearest neighbor search (NNS) in the classical RRT. The experimental results show that under the same experimental conditions, the improved RRT algorithm reduces the computing time by 89.5% compared with the two-way RRT algorithm, which can improve the efficiency of computing time and the quality of searching path, and has a certain reference value.