Abstract: To solve the path planning problem of autonomous underwater vehicles under the condition of inaccurate ocean current prediction and uncertain position information of danger sources, this paper proposes a global path planning method based on the interval multi-objective quantum particle swarm optimization algorithm. The uncertainty ranges of both ocean currents and danger source positions are expressed as interval numbers and the sailing time interval and danger interval of each path are calculated. Based on the interval possibility model, the dominant relationship between intervals is defined, the interval overlap degree and the interval volume are introduced to calculate the interval crowding degree to sort the optimal solutions, an external reserve set is established to save the optimal solution set, and the path position is optimized through the quantum particle swarm optimization algorithm. The simulation results show that, compared with the conventional multi-objective path planning algorithm, the proposed algorithm can find a set of paths with diversified distribution under the condition of multiple uncertain constraints.