Planning Complex Flight Missions for Groups of Intelligent Unmanned Aerial Vehicles

摘要

Parallel and pipeline methods for performing complex flight missions by groups of intelligent unmanned aerial vehicles (UAVs) are comparatively analyzed to find the most effective way for performing such missions under the criteria of minimum time and limited functionality of onboard computers. A model of knowledge representation for planning goal-oriented behavior in the a priori undescribed problem environment regardless of the specific domain is proposed. Procedures for knowledge processing and inference on semantic networks are developed for planning goal-oriented behavior of intelligent UAVs in the process of performing various subtasks of a complex flight mission with polynomial complexity.