In this paper, a 2-D mission planning approach is developed for UAV applications. The main contribution of the paper is the development of an extension to the Bellman Ford algorithm that enables incorporation of constraints directly into the algorithm during run time. The dynamical constraints of the vehicle, such as its angle of turn, can therefore be catered for. Furthermore, a procedure for computing a number of sub-optimal paths is developed so that a range of options is available to the user for selection. These sub-optimal paths are generated in an order of priority (optimality). An objective function is developed which models different conflicting objectives in a unified framework; different objectives can be assigned different weights. The objectives may include minimizing the length of the path, keeping the path as straight as possible, flying over areas of interest, etc. The algorithm is integrated into a software package and tested for complex mission objectives, and results are discussed.
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