Development of a landing algorithm for autonomous underwater vehicles using laser profiling

The autonomous underwater vehicle has proven to be a useful tool for ocean research. However detailed seafloor observations such as microscopic analysis of sand grain structure or study of microbial colonies require a platform with stable footing on the seafloor, which cannot be provided by a cruising type AUV. In this research the authors propose a new class of AUV, capable of landing to provide a stable, but mobile, platform with which to perform these observations. This paper proposes a sensing system and a software algorithm to enable the AUVs to perform landing. A light sectioning based method is used to scan the seafloor with high resolution. Since the seafloor can change abruptly and at short intervals, the reliability and functioning of such technology requires real-time seafloor classification and detection of suitable landing sites. A landing algorithm has been developed which uses three dimensional bathymetry data and calculates a landing vector coordinate in real-time. A microscope sensor payload developed to obtain magnified images of the seafloor after landing has also been tested. Data from sea experiments are presented, where the algorithm demonstrated real-time generation of landing vector coordinates for an ROV.