Route planning of unmanned aerial vehicle in post-disaster underground based on improved algorithm

In view of problems of redundant search point and poor real-time performance when encountering sudden threat existed in application of traditional algorithm in route planning of unmanned aerial vehicle in environment detection for post-disaster underground, a reverse variable weight sparse algorithm was proposed. According to performance constraint of unmanned aerial vehicle and threat model in post-disaster underground, global static route planning is carried out from target point to start point, so as to avoid a large number of invalid searches. Different weight coefficients are set according to mission requirement of unmanned aerial vehicle, so as to obtain route focuses on distance or safety. Only the path covered by sudden threat is corrected by introducing sub-target point strategy, so as to avoid sudden threat effectively in short time. The simulation results show that the algorithm used in route planning can save time of route planning and reduce threat to unmanned aerial vehicle, which can effectively guarantee real-time performance and safety of route planning.