Automated Mission Planning via Evolutionary Algorithms

Englander, Jacob A.; Conway, Bruce A.; Williams, Trevor

doi:10.2514/1.54101

Cited by 111 publications

(84 citation statements)

References 11 publications

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“…The outer-loop therefore has an equal probability of selecting "no flyby" for each opportunity as it does to select a flyby. This technique has been shown to be very effective for designing multi-flyby interplanetary missions and has been used to reproduce the Cassini [11] trajectory.…”

Section: A Outer-loop Transcriptionmentioning

confidence: 99%

“…A "null-gene" technique is used to choose the number and identity of flyby bodies [11]. The analyst provides a list of acceptable flyby bodies and a maximum number of flybys for each journey.…”

Section: A Outer-loop Transcriptionmentioning

confidence: 99%

“…The GA was previously applied by these authors to the HOCP of chemical propulsion trajectory design [11].…”

Section: B Outer-loop Optimization Via Gamentioning

confidence: 99%

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Automated Solution of the Low-Thrust Interplanetary Trajectory Problem

Englander

Conway

2017

Journal of Guidance, Control, and Dynamics

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Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. In addition, a time-history of control variables must be chosen that defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated, which can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a hybrid optimal control problem. The method is demonstrated on hypothetical missions to Mercury, the main asteroid belt, and Pluto.

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Section: A Outer-loop Transcriptionmentioning

confidence: 99%

Section: A Outer-loop Transcriptionmentioning

confidence: 99%

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Automated Solution of the Low-Thrust Interplanetary Trajectory Problem

Englander

Conway

2017

Journal of Guidance, Control, and Dynamics

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“…As such, their approach was necessarily limited to the idealized two-body problem of Keplerian theory and lacked the ability to incorporate sources perturbations that arise in LEO scenarios. More recently, Englander et al [3] and Izzo et al [8] utilized EC to design highly complex mission trajectories. Specifically, Englander et al devised a computational methodology using multi-objective genetic algorithms to perform automated interplanetary mission design, whereas Izzo et al designed a mission trajectory among the Galilean moons of Jupiter that optimized observational conditions at time of spacecraft at the time of flyby.…”

Section: Introductionmentioning

confidence: 99%

“…evolutionary computing (EC) and optimization has since emerged as a means for dealing with highly constrained mission profiles for primarily interplanetary trajectories. Evolutionary methods utilized have included genetic algorithms [2,3], particle swarm optimization [4], monotonic basin hopping [5], simulated annealing [6], and differential evolution [7]. To a lesser extent, EC methods have also been leveraged for in-orbit trajectory planning about planets [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Approach to Lambert’s Problem for Non-Keplerian Spacecraft Trajectories

Hinckley

Hitt

2017

Aerospace

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Abstract:In this paper, we use differential evolution (DE), with best-evolved results refined using a Nelder-Mead optimization, to solve boundary-value complex problems in orbital mechanics relevant to low Earth orbits (LEO). A class of Lambert-type problems is examined to evaluate the performance of this evolutionary method in its application to solving nonlinear boundary value problems (BVP) arising in mission planning. In this method, we evolve impulsive initial velocity vectors giving rise to intercept trajectories that take a spacecraft from given initial position in space to specified target position. The positional error of the final position is minimized subject to time-of-flight and/or energy (fuel) constraints. The method is first validated by demonstrating its ability to recover known analytical solutions obtainable with the assumption of Keplerian motion; the method is then applied to more complex non-Keplerian problems incorporating trajectory perturbations arising in low Earth orbit (LEO) due to the Earth's oblateness and rarefied atmospheric drag. The viable trajectories obtained for these challenging problems demonstrate the ability of this computational approach to handle Lambert-type problems with arbitrary perturbations, such as those occurring in realistic mission trajectory design.

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Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects

Araguz

Bou-Balust

Alarcón

2018

Systems Engineering

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While monolithic satellite missions still pose significant advantages in terms of accuracy and operations, novel distributed architectures are promising improved flexibility, responsiveness and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite networks or heterogeneous constellations hybridizing small-spacecraft nodes with high-performance satellites are becoming feasible and advantageous alternatives requiring the adoption of new operation paradigms that enhance their autonomy. While autonomy is a notion that is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic in Distributed Satellite Systems. In this context, this paper focuses on the motivations for system-level autonomy in DSS and justifies its need as an enabler of system qualities.Autonomy is also presented as a necessary feature to bring new distributed Earth observation functions (which require coordination and collaboration mechanisms) and to allow for novel structural functions (e.g. opportunistic coalitions, exchange of resources or in-orbit data services).Mission Planning and Scheduling frameworks (MPS) are then presented as a key component to * Corresponding author. E-mail addresses: {carles.araguz, elisenda.bou, eduard.alarcon}@upc.edu 1 implement autonomous operations in satellite missions. An exhaustive knowledge classification explores the design aspects of MPS for DSS, and conceptually groups them into: components and organizational paradigms; problem modeling and representation; optimization techniques and metaheuristics; execution and runtime characteristics; and the notions of tasks, resources and constraints. This paper concludes by proposing future strands of work devoted to study the tradeoffs of autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that consider some of the limitations of small spacecraft technologies.

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Automated Mission Planning via Evolutionary Algorithms

Cited by 111 publications

References 11 publications

Automated Solution of the Low-Thrust Interplanetary Trajectory Problem

Automated Solution of the Low-Thrust Interplanetary Trajectory Problem

Evolutionary Approach to Lambert’s Problem for Non-Keplerian Spacecraft Trajectories

Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects

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