The Space Station supports the deployment of various payloads for multidisciplinary space science research. Rationally allocating its limited resources to meet the needs of multi-payload missions is crucial for achieving comprehensive benefits. The multi-payload mission planning problem is characterized by the uncertainty of missions. Robustness is a key indicator for planning under uncertainty, but existing methods still have deficiencies in handling uncertain mission planning models. This paper focuses on robust planning models for Space Station multi-payload mission planning. Based on free slack time and redundancy concepts, we establish robustness indicators based on redundancy factors. On this basis, we mathematically describe the problem’s constraints, objective functions, and decision variables, establishing an optimization model for multi-payload mission planning based on redundancy factors. Multi-objective differential evolution algorithm was used to solve the model and compare the results with a robustness model based on mission duration. Experiments show that the robustness model based on redundancy factors can effectively improve the robustness of planning schemes, achieving stable comprehensive benefits under the interference of unexpected events.