We present an open\u2010source system for Micro\u2010Aerial Vehicle\u00a0(MAV) autonomous navigation from vision\u2010based sensing. Our system focuses on dense mapping, safe local planning, and global trajectory generation, especially when using narrow field\u2010of\u2010view sensors in very cluttered environments. In addition, details about other necessary parts of the system and special considerations for applications in real\u2010world scenarios are presented. We focus our experiments on evaluating global planning, path smoothing, and local planning methods on real maps made on MAVs in realistic search\u2010and\u2010rescue and industrial inspection scenarios. We also perform thousands of simulations in cluttered synthetic environments, and finally validate the complete system in real\u2010world experiments.<\/p>\n","protected":false},"excerpt":{"rendered":"
We present an open\u2010source system for Micro\u2010Aerial Vehicle\u00a0(MAV) autonomous navigation from vision\u2010based sensing. Our system focuses on dense mapping, safe local planning, and global trajectory generation, especially when using narrow field\u2010of\u2010view sensors in very cluttered environments. In addition, details about other necessary parts of the system and special considerations for applications in real\u2010world scenarios are […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"4","msr_journal":"Journal of Field 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