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Conventional trajectory design techniques for space exploration
missions rely strongly upon Kepler's analytical description of orbital
motion about a single spherical body or upon special classes of
trajectories that are well-studied for the case of two such bodies.
However, these techniques do not generalize well to the case of
asteroids and comets -- small bodies of high scientific value -- due
to the strongly unintuitive and non-periodic orbital motion produced
by their irregular gravity fields. To overcome these limitations, an
alternate approach to trajectory design is explored that employs
techniques from robotics, non-linear control, and AI path planning.
Sampling-based planning is conducted via heuristic search of a control
domain that represents a set of single-impulse spacecraft maneuvers,
efficiently identifying actions that produce high performance in terms
of science objectives and safety constraints. Implementation of this
design scheme in a receding-horizon manner with a cost-to-go heuristic
ultimately produces low-frequency control sequences and resulting
complex motion that enable ambitious close-proximity science
operations while mitigating substantial estimation errors
characteristic of small body missions.