The Route-planning Algorithm Of Multi-unmanned Aerial Vehicle Which Can Adapt Variable Threat

Multi-unmanned aerial vehicle’s collaborative route planning is that eachunmanned aerial vehicle’s path planning meet the task’s requirements for the sametarget within a certain period of time,that is the multi-unmanned aerial vehicle’stechnology who based on the time collaboration. For each aircraft, the planning costlowly is hoped in the progress of the route planning, and the collaborative routeplanning is hoped best as well. Therefore, an effective strategy is needed to solve theproblem. In addition, aircraft’s route planning. must be real-time because of theenvironmental variability in the progress of the aircraft flying. For the purpose, thispaper puts forward a multi-unmanned route planning algorithm which can adapt tovarious sorts of hazardous environments.For each aircraft’s route planning, the3D route planning algorithm based onthe sparse A*is put forward in the initial phase. The algorithm cost as lowly aspossible to meet the demand of the route planning. Because of the influence ofthreaten by dynamically changes, aircraft’s route planning algorithm based on thehigh probability of matching points evolution is put forward. The high probabilityof matching notes has been extended without dangerous by notes expending formerly.The algorithm meet the demand of the route planning fast and real time, and thelatter’s cost after several evolutions is accept.For multi-unmanned aircraft’s collaborative route planning, the route planningalgorithm based on time collaboration is put forward in the initial phase. Thealgorithm must complete the of all aircrafts’ route planning in accordance with theplanning principles of each track in proper order. The algorithm makes sure eachaircraft in the air as fast as possible, and achieve the target finally at the same time.During the flight, if a vehicle is encountered new threats, the route planning algorithmbased on time collaboration is put forward. It still makes sure the aircrafts achievethe target at the same time after planning for the new track. The algorithm makes surecollaboration by re-coordinating the speed of each vehicle to avoid the problem thatother non-threat vehicles may fly more after the re-planning. The experimental data shows that the cost of multi-unmanned aircraft’scollaborative route planning is lowest, and meet the principle of dispersion,and thecollaboration based on time is the best. It also can effectively re-plan the track afterbe influenced by variable threats. Re-planning the path is the best approximately andmeet the requirements real-time and reach the target under the conditions oftime-based collaborative finally.