Multiple-objective motion planning for unmanned aerial vehicles

Here we consider the problem of low-flying rotorcraft that must perform various missions such as navigating to specific goal points while avoiding obstacles, looking for acceptable landing sites or performing continuous surveillance. Not all of such missions can be expressed as safe, goal seeking, partly because in many cases there isn't an obvious goal. Rather than developing singular solutions to each mission, we seek a generalized formulation that enables us to express a wider range of missions. Here we propose a framework that allows for multiple objectives to be considered simultaneously and discuss corresponding planning algorithms that are capable of running in realtime on autonomous air vehicles. The algorithms create a set of initial hypotheses that are then optimized by a sub-gradient based trajectory algorithm that optimizes the multiple objectives, producing dynamically feasible trajectories. We have demonstrated the feasibility of our approach with changing cost functions based on newly discovered information. We report on results in simulation of a system that is tasked with navigating safely between obstacles while searching for an acceptable landing site.