Angelo Oddi

The RAXEM Tool on Mars Express - Uplink Planning Optimisation and Scheduling Using AI Constraint Resolution

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.

Science Operations Pre-Planning & Optimization using AI constraint-resolution - the APSI Case Study 1

This paper gives a preliminary overview on activities within an ongoing project aimed at building a planning and scheduling software framework to support mission planners in ∞exibly support operations in ESA missions. These recent developments are in the scope of the Advanced Planning and Scheduling Initiative (APSI) an activity funded by ESA/ESOC and started in late 2006. In particular we describe here the test of the software framework in developing a support tool for Long and Medium Term Planning for Mars Express. The goal of this study, also know as Case Study 1 for APSI, is to generate a pre-optimized skeleton plan for science, communication and spacecraft maintenance slots, to be used as a support in the dialogue between the science and operation team in early pre-planning of activities. This problem has been identifled as an example of time consuming process that can potentially beneflt from the use of a support tool that performs a plan optimization phase.

A Formal Domain Description Language for a Temporal Planner

The Domain Description Language (DDL) is the basic knowledge representation service in any problem solving architecture. This paper introduces DDL.1 a DDL for a planning and schednling architecture that adopts basic features from control theory and extends them to the specification of constraints. A general overview of the language is given, its syntax and semantics described. Finally, the problem of temporal planning by using such a language is briefly addressed.

Human—machine cooperation in space environments

Space mission environments are characterized by the presence of both human operators and advanced automated technology. One relevant aspect in this context is the degree of interaction between these two entities and, in particular, the role of the human agent with respect to his/her collaboration with potentially overwhelming technology. In designing innovative work environments, a certain degree of freedom must be maintained to allow humans and machines to cooperate and adapt to unforeseen contingencies. This paper describes a human — machine cooperation approach to address some of the new challenges introduced by user — system interaction in space missions. Specifically, we will elaborate on the need of retaining a level of flexibility in subdividing responsibilities between autonomous systems and human operators by encouraging the development of mixed systems that integrate the capabilities of both entities. Based on our experience in developing frameworks for space missions, we briefly report on two examples of decision-support tools, pointing out the human aspects that need to be taken into account as well as the beneficial effects of synergies between technology developers and experts in different fields like Cognitive Psychology and Human Computer Interaction. While the described experiences are mainly related to space mission control centres, the detected problems as well as the proposed solutions are, to some extent, extensible to manned missions in outer space.