LAUSR

Abstract Modern approaches for exploration path planning generally do not assume any structural information regarding the operational area. Therefore, they offer good performance when the region of interest is entirely unknown. However, for some applications such as plantation forest surveying, partial information regarding the survey area is known before the exploration process. Because the region of interest consists only of the lower portions of the tree stems themselves, the ground and high-elevation sections of the environment are unimportant and do not need to be observed. Due to these unconventional conditions, existing methods favoring faster survey speeds produce suboptimal surveys as they do not try and ensure even coverage across the entire exploration volume, while methods that favor reconstruction accuracy produce excessively long survey times. This work proposes a structured exploration approach specifically for plantation forests utilizing a lawnmowing pattern to maximize coverage while minimizing re-visited regions, guiding the unmanned aerial vehicle to visit all areas. Experiments are conducted in various environments, with comparisons made to state-of-the-art exploration planners regarding survey time and coverage. Results suggest that the proposed methods produce surveys with significantly more predictable coverage and survey times at the expense of a longer survey.