| Summary: | 碩士 === 國立臺灣科技大學 === 資訊工程系 === 104 === In this paper, we present a monocular vision-based autonomous exploration system by using an open source platform quadcopter. The main propose of this system is building reconstruction which based on a semi-dense point cloud model in automation. This automationsystemcansubstitutethehumanworks. Inthepast,theseworksmightencounter somecriticalproblems. Whenthequadcopterfliedbehindabuildingandtheoperatordoes nottakecorrectiveaction,itmaycauseweakcommunicationsignal. Theseproblemscan be overcome by developing a self-aware autonomous system. In our system, we use a visual-basedSLAMsystemandproposeanavigationsystemtoexploreun-scannedparts of a building. We develop our incremental motion planning method and use a point distributed estimation method for on-line detecting the weak part of the current point cloud modelineachoccupancymaplayer. Accordingtoformerdetectedresults,wesetuprescantrajectorytofixtheweakpart. Inourexperiments,weutilizedifferencesbetweenthe cloud-to-clouddistanceandtiledmodelresolutiontocomparethemanualwithautoflight reconstructionresults.
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