AbstractGiven a set of celestial bodies, the problem of finding an optimal sequence of swing-bys, deep space manoeuvres (DSM) and transfer arcs connecting the elements of the set is combinatorial in nature. The number of possible paths grows exponentially with the number of celestial bodies. Therefore, the design of an optimal multiple gravity assist (MGA) trajectory is a NP-hard mixed combinatorial–continuous problem. Its automated solution would greatly improve the design of future space missions, allowing the assessment of a large number of alternative mission options in a short time. This work proposes to formulate the complete automated design of a multiple gravity assist trajectory as an autonomous planning and scheduling problem. The resulting scheduled plan will provide the optimal planetary sequence and a good estimation of the set of associated optimal trajectories. The trajectory model consists of a sequence of celestial bodies connected by two-dimensional transfer arcs containing one DSM. For each transfer arc, the position of the planet and the spacecraft, at the time of arrival, are matched by varying the pericentre of the preceding swing-by, or the magnitude of the launch excess velocity, for the first arc. For each departure date, this model generates a full tree of possible transfers from the departure to the destination planet. Each leaf of the tree represents a planetary encounter and a possible way to reach that planet. An algorithm inspired by ant colony optimization (ACO) is devised to explore the space of possible plans. The ants explore the tree from departure to destination adding one node at the time: every time an ant is at a node, a probability function is used to select a feasible direction. This approach to automatic trajectory planning is applied to the design of optimal transfers to Saturn and among the Galilean moons of Jupiter. Solutions are compared to those found through more traditional genetic-algorithm techniques.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    MGA trajectory planning with an ACO-inspired algorithm


    Contributors:

    Published in:

    Acta Astronautica ; 67 , 9-10 ; 1202-1217


    Publication date :

    2010-07-05


    Size :

    16 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    MGA trajectory planning with an ACO-inspired algorithm

    Ceriotti, Matteo | Online Contents | 2010


    Trajectory planning method and trajectory planning algorithm for an aerial vehicle

    ORTLIEB MARKUS / ADOLF FLORIAN-MICHAEL | European Patent Office | 2023

    Free access

    TRAJECTORY PLANNING METHOD AND TRAJECTORY PLANNING ALGORITHM FOR AN AERIAL VEHICLE

    ORTLIEB MARKUS / ADOLF FLORIAN-MICHAEL | European Patent Office | 2021

    Free access


    Decision Making and Trajectory Planning for Lane Change Control Inspired by Parallel Parking

    Lanie, Abi / Xiong, Cenbo / Liang, Guanqun et al. | SAE Technical Papers | 2020