• Home
  • Current congress
  • Public Website
  • My papers
  • root
  • browse
  • IAC-14
  • C1
  • 9
  • paper
  • Incremental Planning of Multi-Gravity Assist Trajectories

    Paper number

    IAC-14,C1,9,2,x25603

    Author

    Mr. Juan Manuel Romero Martin, University of Strathclyde, United Kingdom

    Author

    Mr. Luca Masi, Univeristy of Strathclyde, United Kingdom

    Coauthor

    Dr. Massimiliano Vasile, University of Strathclyde, United Kingdom

    Coauthor

    Dr. Edmondo Minisci, University of Strathclyde, United Kingdom

    Coauthor

    Dr. Richard Epenoy, Centre National d'Etudes Spatiales (CNES), France

    Coauthor

    Mr. Vincent Martinot, Thales Alenia Space France, France

    Coauthor

    Dr. JORDI FONTDECABA BAIG, Thales Alenia Space France, France

    Year

    2014

    Abstract
    The paper presents a novel algorithm for the automatic planning and scheduling of multi-gravity assist trajectories (MGA). The algorithm translates the design of an MGA transfer into a planning and scheduling process in which each planetary encounter is seen as a scheduled task.  All possible transfers form a directional graph that is incrementally built and explored simultaneously forward from the departure planet to the arrival one and backward from the arrival planet to the departure one. Nodes in the graph (or tree) represent tasks (or planetary encounters).
    
    
    Backward and forward generated transfers are then matched during the construction of the tree to improve both convergence and exploration. It can be shown, in fact, that the multi-directional exploration of the tree, allows for better quality solutions for the same computational cost.
    
    
    Unlike branch and prune algorithms that use a set of deterministic branching and pruning heuristics, the algorithm proposed in this paper progressively builds a probabilistic model over all the possible tasks that form a complete trajectory. No branch is pruned but the probability of selecting one particular task increases as the algorithm progresses in the search for a solution.
    
    
    The effectiveness of the algorithm is demonstrated on the design optimisation of the trajectory of Marco Polo and JUICE.
    Abstract document

    IAC-14,C1,9,2,x25603.brief.pdf

    Manuscript document

    IAC-14,C1,9,2,x25603.pdf (🔒 authorized access only).

    To get the manuscript, please contact IAF Secretariat.