The sun–Jupiter Trojan asteroid swarms are targets of interest for robotic spacecraft missions, where low-thrust propulsion systems offer a viable approach for realizing tours of these asteroids. This investigation introduces a novel scheme for the automated creation of prospective tours under the natural dynamics of a multibody regime with thrust supplied by a variable-specific-impulse engine. The procedure approximates tours by combining independently generated fuel-optimal rendezvous arcs between asteroid pairs into a series of trajectory legs. Propellant costs as well as departure and arrival times are estimated from the performance of the individual thrust arcs. Tours of interest are readily constructed in higher-fidelity models, and options for the end-to-end trajectories are easily assessed. In this investigation, scenarios where constant and varying-power sources are available to the low-thrust engine are explored. In general, the automation procedure rapidly generates a large number of potential tours and supplies reasonable cost estimates for preliminary baseline mission design. Computational aspects of the design procedure are automated such that end-to-end trajectories are generated with a minimum of human interaction after key elements associated with a proposed mission concept are specified.


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    Title :

    Automated Design of Propellant-Optimal, Low-Thrust Trajectories for Trojan Asteroid Tours


    Contributors:

    Published in:

    Publication date :

    2014-04-17


    Size :

    17 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    Automated Design of Propellant-Optimal, End-to-End, Low-Thrust Trajectories for Trojan Asteroid Tours (AAS 13-492)

    Stuart, J. / Howell, K. / Wilson, R. et al. | British Library Conference Proceedings | 2013



    Design of End-to-End Trojan Asteroid Rendezvous Tours Incorporating Scientific Value

    Stuart, Jeffrey R. / Howell, Kathleen C. / Wilson, Roby S. | AIAA | 2016