Aiming at the problem of energy-saving motion path planning of the mobile robot in a complex unknown environment with mobile robots and multiple narrow channels, a hybrid algorithm based on the heterogeneous multi-objective differential evolution-dynamic window algorithm (HMODE-DWA) is proposed. Firstly, a three-objective optimization model of travel time, actuator force and smoothness is established. Secondly, a heterogeneous multi-objective differential evolution algorithm with collision constraints is designed to optimize three objective functions to obtain the Pareto frontier in a known static envoronment, and then, the optimal global path can be obtained using the average membership function. Thirdly, the robot uses the fuzzy dynamic window algorithm based on the environment buffer area to avoid obstacles in the unknown dynamic and complex environment. The global path nodes have been planned and used as the target points of the local planning for the robots to dynamically avoid obstacles and obtain the global optimal path. Finally, simulation experiments are given to verify the effectiveness of the proposed algorithm. The simulation results show that the proposed hybrid path planning control strategy can obtain the optimal global path and reduce the energy consumption during the dynamic obstacle avoidance process of mobile robots.