000232071 001__ 232071
000232071 005__ 20190722163239.0
000232071 037__ $$aSTUDENT
000232071 245__ $$aAccuracy Prediction in Aerial Mapping
000232071 269__ $$a2017
000232071 260__ $$c2017
000232071 336__ $$aStudent Projects
000232071 520__ $$aLow cost and low weight unmanned aerial vehicle (UAV) systems with imaging capability have enjoyed a rapid development over the past years and are increasingly deployed as carriers for mapping purposes. They present a well-established tool for local-area remote sensing in the fields of agriculture, forestry, mining and hydrology as well as in scientific research. An important part of MAV mapping system is the ground station with a mission planner which serves for flight scheduling and mission execution. The traditional mission planners for MAVs are not dedicated to precise photogrammetry in complicated terrain. They allow planning and executing of autonomous flight as well as setting up of the autopilot systems. However, they lack functions for advanced flight planning, such as those motivated by achieving certain precision and reliability of the determined coordinates of features within the mapped area. The goal of this work is to create a software tool that given a planned trajectory (i.e. planned position and orientation of camera exposure), preliminary digital elevation model (DEM), assumptions on surface texture (i.e. number, distribution and accuracy of image observations) and (optionally) a certain number and distribution of ground control points (GCPs), allow to quantify the quality of the mapping.
000232071 6531_ $$aUAV
000232071 6531_ $$aPrecise mapping
000232071 6531_ $$aoptimization
000232071 6531_ $$asoftware engineering
000232071 700__ $$0(EPFLAUTH)223864$$g223864$$aJospin, Laurent Valentin
000232071 720_2 $$aSkaloud, Jan$$edir.$$g126005$$0240410
000232071 8564_ $$zPublisher's version$$yPublisher's version$$uhttps://infoscience.epfl.ch/record/232071/files/JOSPIN_PDM%20PRINTEMPS%202017.pdf$$s124074192
000232071 8564_ $$uhttps://infoscience.epfl.ch/record/232071/files/JOSPIN_POSTER%20PDM%2016-17.pdf$$s6845601
000232071 909CO $$pENAC$$qGLOBAL_SET$$ooai:infoscience.tind.io:232071
000232071 909C0 $$pSSIE$$0252601$$xU10216
000232071 917Z8 $$x145925
000232071 917Z8 $$x145925
000232071 937__ $$aEPFL-STUDENT-232071
000232071 973__ $$aEPFL
000232071 980__ $$bMASTERS$$aSTUDENT