An optimal control approach to mission planning problems: a proof of concept
Greenslade, Joseph Micheal
Ross, I. Michael
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This work introduces the use of optimal control methods for simultaneous target sequencing and dynamic trajectory planning of an autonomous vehicle. This is achieved by deriving a control solution that minimizes a cost to maximize target selection. In the case of varying target priorities, the method described here preferentially selects higher priority targets to maximize total benefit in the allowed time horizon. Traditional techniques employ heuristic techniques for target sequencing and then apply a separate trajectory planning process to check the feasibility of the sequence for the given vehicle dynamics. This work uses pseudospectral methods to deterministically solve the problem in a single step. The historic barrier to the application of optimal control solutions to the target sequencing problem has been the requirement for a problem formulation built from continuous constraints. Target points are, by their nature, discrete. The key breakthrough is to transform the discrete problem into a continuous representation by modeling targets as Gaussian distributions. The proposed approach is successfully applied to several benchmark problems. Thus, several variations of the so-called motorized travelling salesman problem, including ones in which it is impossible to acquire all the targets in the given time, are solved using the new approach.
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