The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform

Nicola Policella - One of the best experts on this subject based on the ideXlab platform.

  • an innovative product for space mission planning an a posteriori evaluation
    International Conference on Automated Planning and Scheduling, 2007
    Co-Authors: Amedeo Cesta, Gabriella Cortellessa, Simone Fratini, Angelo Oddi, Nicola Policella
    Abstract:

    This paper describes MEXAR2, a software tool that is currently used to synthesize the operational commands for data downlink from the on-Board Memory of an interplanetary space mission spacecraft to the ground stations. The tool has been in daily use by the Mission Planning Team of MARS EXPRESS at the European Space Agency since early 2005. Goal of this paper is to present a quick overview of how the planning and scheduling problem has been addressed, a complete application customized and put into context in the application environment. Then it concentrates on describing more in detail how a core solver has been enriched to create a tool that easily allows users to generate diversified plans for the same problem by handling a set of control parameters, called heuristic modifiers, that insert heuristic bias on the generated solutions. A set of experiments is presented that describes how such modifiers affect the solving process.

  • ICAPS - An innovative product for space mission planning an a posteriori evaluation
    2007
    Co-Authors: Amedeo Cesta, Gabriella Cortellessa, Simone Fratini, Angelo Oddi, Nicola Policella
    Abstract:

    This paper describes MEXAR2, a software tool that is currently used to synthesize the operational commands for data downlink from the on-Board Memory of an interplanetary space mission spacecraft to the ground stations. The tool has been in daily use by the Mission Planning Team of MARS EXPRESS at the European Space Agency since early 2005. Goal of this paper is to present a quick overview of how the planning and scheduling problem has been addressed, a complete application customized and put into context in the application environment. Then it concentrates on describing more in detail how a core solver has been enriched to create a tool that easily allows users to generate diversified plans for the same problem by handling a set of control parameters, called heuristic modifiers, that insert heuristic bias on the generated solutions. A set of experiments is presented that describes how such modifiers affect the solving process.

  • IEA/AIE - From demo to practice the MEXAR path to space operations
    Advances in Applied Artificial Intelligence, 2006
    Co-Authors: Amedeo Cesta, Gabriella Cortellessa, Simone Fratini, Angelo Oddi, Nicola Policella
    Abstract:

    This paper describes a software tool that synthesizes commands for data downlink from the on-Board Memory of the Mars Express spacecraft to the ground station. Some features of the tool are depicted, showing how AI techniques for planning, scheduling, domain modeling and intelligent interaction have been put into context in a challenging application environment. The system is the result of a two steps effort: a first study which produced a demonstration prototype able to capture the main aspects of the problem, and a second effort that has developed a fielded application completely integrated in operations environment. The tool is in daily use by the mission planning team of Mars Express at the European Space Agency since February 2005.

  • A Max-Flow Approach for Improving Robustness in a Spacecraft Downlink Schedule
    2004
    Co-Authors: Angelo Oddi, Nicola Policella
    Abstract:

    In the realm of scheduling problems different sources of uncertainty can invalidate the solutions. In this paper we are concerned with the generation of high quality downlink schedules in a spacecraft domain in presence of a high degree of uncertainty. In particular, we refer to a combinatorial optimization problem called MARS EXPRESS Memory Dumping Problem (MEX-MDP), which arises in the European Space Agency program MARS EXPRESS. A MEXMDP consists in the generation of dumping commands for transferring the whole set of data from the satellite to the ground. The domain is characterized by several kinds of constraints such as, bounded on-Board Memory capacities, limited communication windows over the downlink channels, deadlines and ready times imposed by the principal investigators and different sources of uncertainty e.g., the amount of data generated at each scientific observation or the channel data rate. This work describes a reduction of the MEX-MDP to a Max-Flow problem, such that the problem has a solution when the maximum flow equates the total amount of data to dump. Based on this reduction, an iterative procedure is built to improve the robustness of a solution with respect to the utilization of the on-Board Memory. The underlying idea being that the lower are the peaks in Memory utilization, the higher the ability of facing unexpectedly larger amount of data.

  • Constraint-Based Random Search for Solving Spacecraft Downlink Scheduling Problems
    Multidisciplinary Scheduling: Theory and Applications, 1
    Co-Authors: Angelo Oddi, Amedeo Cesta, Nicola Policella, Gabriella Cortellessa
    Abstract:

    This paper introduces a combinatorial optimisation problem called the Mars Express Memory Dumping Problem (Mex-Mdp), which arises in the European Space Agency programme Mars Express. The domain is characterized by complex constraints concerning bounded on-Board Memory capacities, limited communication windows over the downlink channels, deadlines and ready times imposed by the scientists using the spacecraft instruments. This paper lays out the problem and analyses its computational complexity showing that Mex-Mdp is NP-hard. Then the problem is modelled as a Constraint Satisfaction Problem and two different heuristic strategies for its solution are presented: a core greedy constraint-based procedure and an iterative sampling strategy based on random search. The algorithms are evaluated both against a benchmark set created on the basis of ESA documentation and a lower bound of the minimised objective function. Experimental results show the overall effectiveness of the approach.

Amedeo Cesta - One of the best experts on this subject based on the ideXlab platform.

  • an innovative product for space mission planning an a posteriori evaluation
    International Conference on Automated Planning and Scheduling, 2007
    Co-Authors: Amedeo Cesta, Gabriella Cortellessa, Simone Fratini, Angelo Oddi, Nicola Policella
    Abstract:

    This paper describes MEXAR2, a software tool that is currently used to synthesize the operational commands for data downlink from the on-Board Memory of an interplanetary space mission spacecraft to the ground stations. The tool has been in daily use by the Mission Planning Team of MARS EXPRESS at the European Space Agency since early 2005. Goal of this paper is to present a quick overview of how the planning and scheduling problem has been addressed, a complete application customized and put into context in the application environment. Then it concentrates on describing more in detail how a core solver has been enriched to create a tool that easily allows users to generate diversified plans for the same problem by handling a set of control parameters, called heuristic modifiers, that insert heuristic bias on the generated solutions. A set of experiments is presented that describes how such modifiers affect the solving process.

  • ICAPS - An innovative product for space mission planning an a posteriori evaluation
    2007
    Co-Authors: Amedeo Cesta, Gabriella Cortellessa, Simone Fratini, Angelo Oddi, Nicola Policella
    Abstract:

    This paper describes MEXAR2, a software tool that is currently used to synthesize the operational commands for data downlink from the on-Board Memory of an interplanetary space mission spacecraft to the ground stations. The tool has been in daily use by the Mission Planning Team of MARS EXPRESS at the European Space Agency since early 2005. Goal of this paper is to present a quick overview of how the planning and scheduling problem has been addressed, a complete application customized and put into context in the application environment. Then it concentrates on describing more in detail how a core solver has been enriched to create a tool that easily allows users to generate diversified plans for the same problem by handling a set of control parameters, called heuristic modifiers, that insert heuristic bias on the generated solutions. A set of experiments is presented that describes how such modifiers affect the solving process.

  • IEA/AIE - From demo to practice the MEXAR path to space operations
    Advances in Applied Artificial Intelligence, 2006
    Co-Authors: Amedeo Cesta, Gabriella Cortellessa, Simone Fratini, Angelo Oddi, Nicola Policella
    Abstract:

    This paper describes a software tool that synthesizes commands for data downlink from the on-Board Memory of the Mars Express spacecraft to the ground station. Some features of the tool are depicted, showing how AI techniques for planning, scheduling, domain modeling and intelligent interaction have been put into context in a challenging application environment. The system is the result of a two steps effort: a first study which produced a demonstration prototype able to capture the main aspects of the problem, and a second effort that has developed a fielded application completely integrated in operations environment. The tool is in daily use by the mission planning team of Mars Express at the European Space Agency since February 2005.

  • Planning with Concurrency, Time and Resources: A CSP-Based Approach
    Intelligent Techniques for Planning, 2005
    Co-Authors: Amedeo Cesta, Simone Fratini, Angelo Oddi
    Abstract:

    This chapter proposes to model a planning problem (e.g., the control of a satellite system) by identifying a set of relevant components in the domain (e.g., communication channels, on-Board Memory or batteries), which need to be controlled to obtain a desired temporal behavior. The domain model is enriched with the description of relevant constraints with respect to possible concurrency, temporal limits and scarce resource availability. The paper proposes a planning framework based on this view that relies on a formalization of the problem as a Constraint Satisfaction Problem (CSP) and defines an algorithmic template in which the integration of planning and scheduling is a fundamental feature. In addition, the paper describes the current implementation of a constraint-based planner called OMP that is grounded on these ideas and shows the role constraints have in this planner, both at domain description level and as a guide for problem solving.

  • Constraint-Based Random Search for Solving Spacecraft Downlink Scheduling Problems
    Multidisciplinary Scheduling: Theory and Applications, 1
    Co-Authors: Angelo Oddi, Amedeo Cesta, Nicola Policella, Gabriella Cortellessa
    Abstract:

    This paper introduces a combinatorial optimisation problem called the Mars Express Memory Dumping Problem (Mex-Mdp), which arises in the European Space Agency programme Mars Express. The domain is characterized by complex constraints concerning bounded on-Board Memory capacities, limited communication windows over the downlink channels, deadlines and ready times imposed by the scientists using the spacecraft instruments. This paper lays out the problem and analyses its computational complexity showing that Mex-Mdp is NP-hard. Then the problem is modelled as a Constraint Satisfaction Problem and two different heuristic strategies for its solution are presented: a core greedy constraint-based procedure and an iterative sampling strategy based on random search. The algorithms are evaluated both against a benchmark set created on the basis of ESA documentation and a lower bound of the minimised objective function. Experimental results show the overall effectiveness of the approach.

Angelo Oddi - One of the best experts on this subject based on the ideXlab platform.

  • an innovative product for space mission planning an a posteriori evaluation
    International Conference on Automated Planning and Scheduling, 2007
    Co-Authors: Amedeo Cesta, Gabriella Cortellessa, Simone Fratini, Angelo Oddi, Nicola Policella
    Abstract:

    This paper describes MEXAR2, a software tool that is currently used to synthesize the operational commands for data downlink from the on-Board Memory of an interplanetary space mission spacecraft to the ground stations. The tool has been in daily use by the Mission Planning Team of MARS EXPRESS at the European Space Agency since early 2005. Goal of this paper is to present a quick overview of how the planning and scheduling problem has been addressed, a complete application customized and put into context in the application environment. Then it concentrates on describing more in detail how a core solver has been enriched to create a tool that easily allows users to generate diversified plans for the same problem by handling a set of control parameters, called heuristic modifiers, that insert heuristic bias on the generated solutions. A set of experiments is presented that describes how such modifiers affect the solving process.

  • ICAPS - An innovative product for space mission planning an a posteriori evaluation
    2007
    Co-Authors: Amedeo Cesta, Gabriella Cortellessa, Simone Fratini, Angelo Oddi, Nicola Policella
    Abstract:

    This paper describes MEXAR2, a software tool that is currently used to synthesize the operational commands for data downlink from the on-Board Memory of an interplanetary space mission spacecraft to the ground stations. The tool has been in daily use by the Mission Planning Team of MARS EXPRESS at the European Space Agency since early 2005. Goal of this paper is to present a quick overview of how the planning and scheduling problem has been addressed, a complete application customized and put into context in the application environment. Then it concentrates on describing more in detail how a core solver has been enriched to create a tool that easily allows users to generate diversified plans for the same problem by handling a set of control parameters, called heuristic modifiers, that insert heuristic bias on the generated solutions. A set of experiments is presented that describes how such modifiers affect the solving process.

  • IEA/AIE - From demo to practice the MEXAR path to space operations
    Advances in Applied Artificial Intelligence, 2006
    Co-Authors: Amedeo Cesta, Gabriella Cortellessa, Simone Fratini, Angelo Oddi, Nicola Policella
    Abstract:

    This paper describes a software tool that synthesizes commands for data downlink from the on-Board Memory of the Mars Express spacecraft to the ground station. Some features of the tool are depicted, showing how AI techniques for planning, scheduling, domain modeling and intelligent interaction have been put into context in a challenging application environment. The system is the result of a two steps effort: a first study which produced a demonstration prototype able to capture the main aspects of the problem, and a second effort that has developed a fielded application completely integrated in operations environment. The tool is in daily use by the mission planning team of Mars Express at the European Space Agency since February 2005.

  • Planning with Concurrency, Time and Resources: A CSP-Based Approach
    Intelligent Techniques for Planning, 2005
    Co-Authors: Amedeo Cesta, Simone Fratini, Angelo Oddi
    Abstract:

    This chapter proposes to model a planning problem (e.g., the control of a satellite system) by identifying a set of relevant components in the domain (e.g., communication channels, on-Board Memory or batteries), which need to be controlled to obtain a desired temporal behavior. The domain model is enriched with the description of relevant constraints with respect to possible concurrency, temporal limits and scarce resource availability. The paper proposes a planning framework based on this view that relies on a formalization of the problem as a Constraint Satisfaction Problem (CSP) and defines an algorithmic template in which the integration of planning and scheduling is a fundamental feature. In addition, the paper describes the current implementation of a constraint-based planner called OMP that is grounded on these ideas and shows the role constraints have in this planner, both at domain description level and as a guide for problem solving.

  • A Max-Flow Approach for Improving Robustness in a Spacecraft Downlink Schedule
    2004
    Co-Authors: Angelo Oddi, Nicola Policella
    Abstract:

    In the realm of scheduling problems different sources of uncertainty can invalidate the solutions. In this paper we are concerned with the generation of high quality downlink schedules in a spacecraft domain in presence of a high degree of uncertainty. In particular, we refer to a combinatorial optimization problem called MARS EXPRESS Memory Dumping Problem (MEX-MDP), which arises in the European Space Agency program MARS EXPRESS. A MEXMDP consists in the generation of dumping commands for transferring the whole set of data from the satellite to the ground. The domain is characterized by several kinds of constraints such as, bounded on-Board Memory capacities, limited communication windows over the downlink channels, deadlines and ready times imposed by the principal investigators and different sources of uncertainty e.g., the amount of data generated at each scientific observation or the channel data rate. This work describes a reduction of the MEX-MDP to a Max-Flow problem, such that the problem has a solution when the maximum flow equates the total amount of data to dump. Based on this reduction, an iterative procedure is built to improve the robustness of a solution with respect to the utilization of the on-Board Memory. The underlying idea being that the lower are the peaks in Memory utilization, the higher the ability of facing unexpectedly larger amount of data.

Andre-luc Beylot - One of the best experts on this subject based on the ideXlab platform.

  • VTC Fall - Precomputed Routing in a Store and Forward Satellite Constellation
    2007 IEEE 66th Vehicular Technology Conference, 2007
    Co-Authors: H. Cruz-sanchez, Laurent Franck, Andre-luc Beylot
    Abstract:

    Satellite constellations like Orbcomm provide store and forward message communication services. Inter-satellite links (ISL) are not considered in order to keep the system simple and the costs moderate ([1], [2]). Rather, gateways may act as relays between satellites. In this context, routing is important because it helps to control the end-to-end delay and resources utilization (e.g. on-Board Memory). However, routing must face frequent changes and partitioning of the network because of the satellite motion. Similar routing problems have been studied in the transportation field (e.g. subway and railways). In this contribution, the shortest path problem with time windows (SPPTW) is applied to satellite constellations and a pre-computed routing algorithm is derived. Simulation results show how this algorithm reduces the end-to-end delay of the routes.

Gabriella Cortellessa - One of the best experts on this subject based on the ideXlab platform.

  • an innovative product for space mission planning an a posteriori evaluation
    International Conference on Automated Planning and Scheduling, 2007
    Co-Authors: Amedeo Cesta, Gabriella Cortellessa, Simone Fratini, Angelo Oddi, Nicola Policella
    Abstract:

    This paper describes MEXAR2, a software tool that is currently used to synthesize the operational commands for data downlink from the on-Board Memory of an interplanetary space mission spacecraft to the ground stations. The tool has been in daily use by the Mission Planning Team of MARS EXPRESS at the European Space Agency since early 2005. Goal of this paper is to present a quick overview of how the planning and scheduling problem has been addressed, a complete application customized and put into context in the application environment. Then it concentrates on describing more in detail how a core solver has been enriched to create a tool that easily allows users to generate diversified plans for the same problem by handling a set of control parameters, called heuristic modifiers, that insert heuristic bias on the generated solutions. A set of experiments is presented that describes how such modifiers affect the solving process.

  • ICAPS - An innovative product for space mission planning an a posteriori evaluation
    2007
    Co-Authors: Amedeo Cesta, Gabriella Cortellessa, Simone Fratini, Angelo Oddi, Nicola Policella
    Abstract:

    This paper describes MEXAR2, a software tool that is currently used to synthesize the operational commands for data downlink from the on-Board Memory of an interplanetary space mission spacecraft to the ground stations. The tool has been in daily use by the Mission Planning Team of MARS EXPRESS at the European Space Agency since early 2005. Goal of this paper is to present a quick overview of how the planning and scheduling problem has been addressed, a complete application customized and put into context in the application environment. Then it concentrates on describing more in detail how a core solver has been enriched to create a tool that easily allows users to generate diversified plans for the same problem by handling a set of control parameters, called heuristic modifiers, that insert heuristic bias on the generated solutions. A set of experiments is presented that describes how such modifiers affect the solving process.

  • IEA/AIE - From demo to practice the MEXAR path to space operations
    Advances in Applied Artificial Intelligence, 2006
    Co-Authors: Amedeo Cesta, Gabriella Cortellessa, Simone Fratini, Angelo Oddi, Nicola Policella
    Abstract:

    This paper describes a software tool that synthesizes commands for data downlink from the on-Board Memory of the Mars Express spacecraft to the ground station. Some features of the tool are depicted, showing how AI techniques for planning, scheduling, domain modeling and intelligent interaction have been put into context in a challenging application environment. The system is the result of a two steps effort: a first study which produced a demonstration prototype able to capture the main aspects of the problem, and a second effort that has developed a fielded application completely integrated in operations environment. The tool is in daily use by the mission planning team of Mars Express at the European Space Agency since February 2005.

  • Constraint-Based Random Search for Solving Spacecraft Downlink Scheduling Problems
    Multidisciplinary Scheduling: Theory and Applications, 1
    Co-Authors: Angelo Oddi, Amedeo Cesta, Nicola Policella, Gabriella Cortellessa
    Abstract:

    This paper introduces a combinatorial optimisation problem called the Mars Express Memory Dumping Problem (Mex-Mdp), which arises in the European Space Agency programme Mars Express. The domain is characterized by complex constraints concerning bounded on-Board Memory capacities, limited communication windows over the downlink channels, deadlines and ready times imposed by the scientists using the spacecraft instruments. This paper lays out the problem and analyses its computational complexity showing that Mex-Mdp is NP-hard. Then the problem is modelled as a Constraint Satisfaction Problem and two different heuristic strategies for its solution are presented: a core greedy constraint-based procedure and an iterative sampling strategy based on random search. The algorithms are evaluated both against a benchmark set created on the basis of ESA documentation and a lower bound of the minimised objective function. Experimental results show the overall effectiveness of the approach.