Solving the memory-dumping problem optimally is a difficult combinatorial problem. Additionally, for deep-space missions, the solution entails a set of critical decisions that D eep-space missions carry an ever larger set of different and complementary onboard payloads. Each payload generates data, and synthesizing it for optimized downlinking is one way to reduce the ratio of mission costs

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This paper describes an AI-based application, referred to as RAXEM, which has been developed to support the Flight Control Team of Mars Express in the daily planning task of uplinking telecommands to the spacecraft. The tool is part of the mission improvement activities within the team to move from a manually-oriented to a more tool-assisted and automated approach. As such it not only provides an interactive process for solving the uplink problem but also contributes to reducing the workload of the engineers. A first AI based system, MEXAR2, has been in operational use at ESOC since the beginning of 2005. It was developed to perform the planning of the downlink of the telemetry data. The tool is based on AI constraint resolution techniques and was the first of its kind to be in operational use at ESOC. It has gained wide-spread acclaim in the mission planning and scheduling community. The operational experience and success of MEXAR2 and the similarity of the problem subsequently led to the definition for an application to generate a detailed uplink plan and schedule. Mars Express is a mission that is not operated in real-time but all commands are loaded into the Master Timeline Buffer (MTL) on the spacecraft from where they are executed at the given time-tag. The uplink plan depends on a number of constraints, i.e. the loading profile of the MTL, the available uplink opportunities (or uplink windows) depending on the ground station allocation and spacecraft orientation to Earth (which is determined by the science requirements), the occultations by Mars and moons and the availability of power that determines the activation periods of the spacecraft transmitter. The paper presents the operations and mission planning constraints that influenced the requirements for the RAXEM planning tool. It further focuses on the tool and its operational usage, the iterative-prototyping approach from requirements definition to software development and operational validation, and the optimization and benefits for the Flight Control Team compared to the manual approach adopted up to the introduction of the tool. The paper will also address the issues raised by introducing so-called "clever" tools to help human operators and compare the consequences depending on the target user group, the planners (as for the downlink planning tool, MEXAR2) or the spacecraft engineers (as for RAXEM). Furthermore, another implementation option for the uplink problem based on Operations Research algorithms developed as a student project will be included.

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