Optimal scan planning for surveying large sites with static and mobile mapping systems

Since the last two decades, use of laser scanners for generating accurate and dense 3D models has been rapidly growing in multiple disciplines. The reliance on human-expertise to perform an efficient scanning terms completeness quality encouraged researchers develop strategies carrying out optimized automated scan planning. Nevertheless, due predominant static terrestrial (TLS), most developed methods have focused optimization by fixing standpoints basis scanning. increasing portable mobile systems (MLS) enables faster non-stop acquisition which demands planning optimal trajectories. Therefore, a novel method addressing absence dynamic is proposed considering specific MLS constraints such as maximum time or closed-loops requirement. First, initial analysis carried determinate key-positions reach during data acquisition. From these positions navigable graph generated compute routes satisfying three-step process. This starts estimating number necessary subsequently carry coarse partition based Kmedoids clustering. Next, balancing algorithm was implemented balanced node exchanging. Finally, partitions are extended adding key nodes from their adjacent ones order provide desirable overlapping between scans. tested simulating three scanner configurations four indoor outdoor real case studies. computed evaluated point cloud density with simulator Helios++. • A tool including routing both graph-partitioning programming formulation solving closed loops. route softening towards simulation Helios.