Alessandro Donati

Mexar2: AI Solves Mission Planner Problems

Deep-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 to science return. This is the main role of the Mars-Express scheduling architecture (Mexar2), an Al-based tool in daily use on the Mars-Express mission since February 2005. Mexar2 supports space mission planners continuously as they plan data downlinks from the spacecraft to Earth. The tool lets planners work at a higher abstraction level while it performs low-level, often-repetitive tasks. It also helps them produce a plan rapidly, explore alternative solutions, and choose the most robust plan for execution. Additionally, planners can analyze any problems over multiple days and identify payload overcommitments that cause resource bottlenecks and increase the risk of data losses. Mexar2 has significantly increased the data return over the whole Mars-Express mission duration. Its effectively become a work companion for mission planners at the European Space Agencys European Space Operations Center (ESOC) in Darmstadt, Germany.

From Anomaly Reports to Cases

Creating case representations in unsupervised textual case-based reasoning applications is a challenging task because class knowledge is not available to aid selection of discriminatory features or to evaluate alternative system design configurations. Representation is considered as part of the development of a tool, called CAM , which supports an anomaly report processing task for the European Space Agency. Novel feature selection/extraction techniques are created which consider word co-occurrence patterns to calculate similarity between words. These are used together with existing techniques to create 5 different case representations. A new evaluation technique is introduced to compare these representations empirically, without the need for expensive, domain expert analysis. Alignment between the problem and solution space is measured at a local level and profiles of these local alignments used to evaluate the competenceof the system design.

Enhanced Telemetry Monitoring with Novelty Detection

Typically, automatic telemetry monitoring in space operations is performed by Out-of-Limits (OOL) alarms. This approach consists of defining an upper and lower threshold so that when a measurement goes above the upper limit or below the lower one, an alarm is triggered. We discuss the limitations of the Out-Of-Limits approach and propose a new monitoring paradigm based on novelty detection. The proposed monitoring approach can detect novel behaviors, which are often signatures of anomalies, very early — allowing engineers in some cases to react before the anomaly develops. A prototype implementing this monitoring approach has been implemented and applied to several ESA missions. The operational assessment from the XMM-Newton operations team is presented.

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.

A novel ACO algorithm for dynamic binary chains based on changes in the system's stability

In the last decade, Dynamic Optimization Problems (DOP) have received increasing attention. Changes in the problem structure pose a great challenge for the optimization techniques. The Ant Colony Optimization (ACO) metaheuristic has a number of potentials in this field due to its adaptability and flexibility. However their design and analysis are still critical issues. This is where research on formal methods can increase the reliability of these systems and improve the understanding of their dynamics in complex problems such as DOPs. This paper presents a novel ACO algorithm based on an analytical model describing the long-terms behaviours of the ACO systems in problems represented as binary chains, a type of DOP. These behaviours are described using modelling techniques already developed for studying dynamical systems. The algorithm developed takes advantage of new insights offered by this model to regulate the tradeoff of exploration/exploitation resulting in a ACO system able to adapt its long-term behaviours to the problem changes and to improve its performance due to the experiences learnt from the previous explorations. An empirical evaluation is used to validate the algorithm capabilities of adaptability and optimization.

Rapid Prototyping of Planning & Scheduling Tools

The Advanced Planning and Scheduling Initiative, or APSI, is an ESA programme to design and implement an Artificial Intelligence (AI) software infrastructure for planning and scheduling that can generically support different types and classes of space mission operations. The goal of the APSI is twofold: (1)~creating a software framework to improve the cost-effectiveness and flexibility of mission planning support tool development; (2)~bridging the gap between AI planning and scheduling technology and the world of space mission planning. A key aspect of the success of this project is the presence of a flexible timeline representation module that allows to exploit alternatives in the modeling of mission features. This paper shows an example of such a flexibility by using a real problem in the space realm - the HERSCHEL Science Long Term Planning process.

Designing and Deploying Meaningful Auditory Alarms for Control Systems

In the old days, spacecraft alarming notifications to operators were directed, upon arrival to ground, to one of those needle printers. Trained operators could tell, from the length and rhythm of the printer noise, what kind of alarm it was and therefore infer the criticality or the subject. Today, in monitoring and control systems (MCS) currently in use at the European Space Agency (ESA), there is no care to convey information in the sounds, and these alarm sounds have not been systematically designed to indicate the type of system failure and further elicit the desired and accurate operator response. Operators depend heavily on the graphical interfaces in order to pinpoint the source of alarm sounds (see Fig. 1) which further creates cognitive load. Similarly, switching cost from auditory perception to visual perception while finding the source of the information is undesirable when time can be a precious commodity for operators when monitoring valuable spacecraft. Therefore, ESA teamed up with Delft University of Technology and Plymouth University in order to investigate and design a new auditory display for the control rooms located in the European Space Operations Centre (ESOC), in Darmstadt, Germany

An Automatic Planning and Scheduling System for the Mars Express Uplink Scheduling Problem

This paper describes the algorithms used in a planning and scheduling software tool developed for the European Space Agency in the framework of the Mars Express mission. The planning and scheduling algorithm computes a feasible schedule for the transmission of telecommands (TCs) from the ground segment to the space segment, complying with a number of technical constraints. Owing to the distance between Mars and Earth, it is important that the robustness of the schedule is taken into account because repair operations may be very time consuming or even impossible. For this reason, besides the maximization of the number of TCs transmitted from Earth to Mars, the scheduler is also designed to maximize the number of full confirmations and secondary time windows, which are two special characteristics of the Mars Express schedule explicitly designed for the sake of robustness. Besides the maximization of robustness, the scheduling algorithm that can run with different settings can be used to optimize some secondary figures of merit, such as the average saturation of the memory devices of the space segment and the usage of the time windows available for communication. Computational results on real instances are presented.

Space Weather Services for Space Mission Operations

Systems on board spacecraft have since long manifested their weakness towards the violence of space weather conditions and events. At the European Space Operations Centre, the first step in what concerns the provision of space weather services for operations goes back to 2005 with the implementation of the SEIS prototype, which integrates space weather data with spacecraft data and provides services of real-time and offline data visualization, analysis and correlation, alarming, warning and forecasting, reporting and historical file access. Since then, the evolution of this concept led to the development of a second generation of services to support spacecraft operations, SEISOP, now a precursor service of the European Space Situational Awareness program. This paper presents the evolution of the space weather services provided to operations at ESOC since 2005, the assessment of the benefits verified so far, as well as the expectations for the future and alignment to the SSA program.

SEISOP: A System Enabling Space Weather Services for Space Missions

Henrique Oliveira Solenix Deutschland GmbH, Darmstadt, Germany henrique.oliveira@esa.int Antonio Gutierrez Deimos Engenharia, Lisboa, Portugal antonio.gutierrez@deimos.com.pt Joao Paulo Pimentao Holos, Caparica, Portugal pim@holos.pt Sergio Ibarmia INTA, Madrid, Spain ibarmiahsa@inta.es Antonio Falcao Uninova, Caparica, Portugal ajf@uninova.com Federico di Marco VEGA Deutschland GmbH, Darmstadt, Germany federico.di.marco@esa.int