To address the problems that commercial flight software lacks adaptive image acquisition capability

and that individual unmanned aerial vehicles(UAVs) have limited performance and endurance in large-scale UAV 3D reconstruction tasks

a 3D reconstruction algorithm for buildings based on multi-UAV aerial photography sensor fusion is proposed.In this method

UAVs are equipped with image sensors

and a trajectory planning framework is constructed based on task and search principles.First

the optimal shooting pose is determined by evaluating scene reconfigurability to improve reconstruction quality.Then

task sequences are assigned to multiple UAVs based on minimum turning angle and length features to reduce overall energy consumption.Finally

energy consumption

safety and reconfigurability are integrated into a unified optimization model to achieve multi-UAV collaborative path search.Experimental results show that this method can effectively support multi-UAV collaborative image acquisition and achieve high-quality 3D reconstruction effects while significantly reducing energy costs.