The Exploration Cascade as a Mission Planning Algorithm for AMADEE-24

In both real and analog missions, the crew can only perform activities and experiments outside the habitat for a certain amount of time. This means that the missions and therefore also the planned activities must be planned precisely to perform as many activities and experiments as possible in as short a time as possible. Such planning must consider external factors such as environmental factors, such as temperature or weather conditions, as well as the duration of experiments and dependencies on other experiments or activities. Furthermore, changes can occur continuously during a mission, which can also impact the planned schedule. In previous analog missions, this planning was performed manually, which can be very time-consuming due to the many possible conditions. This paper presents the Exploration Cascade, a mathematical algorithm that considers possible factors to create an optimal mission plan. Using the analog Mars mission AMADEE-24 as an example, we examine what results this algorithm can achieve and how flexibly it can react to changes, such as changes in weather forecasts or unforeseeable events, such as the failure of scientific equipment. Furthermore, we examined how the efficiency of the algorithm compares with manual planning and what conclusions can be drawn from it.