A novel approach to register sonar data for underwater robot localization

摘要

This paper proposes a novel approach to perform underwater robot localization using sonar data. The proposal relies on two key points: 1) the processing of the sonar measurements to build probabilistic point clouds; and 2) the registration of these point clouds. These key points are achieved by means of an acoustic model that removes the effects of the uneven ensonification followed by a probabilistic interpretation of the sonar measurements. Also, a registration algorithm is presented and used to match consecutively gathered scans in order to globally localize an autonomous underwater vehicles (AUV).