We investigate an exploration problem when constructing complete 3D models in an unknown environment using a Micro-Aerial Vehicle (MAV). Most previous exploration methods were based on the Next-Best-View (NBV) approaches, which iteratively determine the most informative view that exposes the greatest unknown area from the current partial model. However, these approaches sometimes miss minor unreconstructed regions like holes or sparse surfaces (while these can be important features). Furthermore, because the NBV methods iterate the next-best path from a current partial view they sometimes produce unnecessarily long trajectories by revisiting known regions.

Related publications

1. S Song, D Kim, S Jo, Online Coverage and Inspection Planning for 3D Modeling System, Autonomous Robots, 44(8): 1431-1450, 2020 [LINK] [PDF]

Categories: Robotic Intelligence