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Integrated Planning and Control of Rotary-wing Unmanned Aerial Vehicle Navigation

This paper presents an integrated planning and control algorithm for the navigation of an autonomous rotarywing unmanned aerial vehicle in a cluttered environment. The model predictive control combined with a potential fieldlike function integrates planning and control in a single step. This strategy enables the generation of dynamically feasible motion because the planning is done in the action space of the rotary-wing unmanned aerial vehicle. Moreover, it is able to respond promptly to abrupt changes in the environment because the reactive obstacleavoidance method only considers local sensory information. Finally, the shortsightedness of control-based reactive methods can be relieved by the larger planning horizon of the model predictive control. Simulation results show that the proposed integrated planning and controlmethod can complete the navigationmission successfully in a cluttered environment, and it can be applicable to more complicated missions, such as weed surveillance and management.