Underwater place recognition using forward-looking sonar images: A topological approach

摘要

Autonomous underwater vehicles are a prominent tool for underwater exploration because they can access dangerous places avoiding the risks for the human beings. However, the autonomous navigation still a challenge due to the characteristics of the environment that decrease the performance of the sensor and the robot perception. In this context, this paper proposes a loop closure detector addressed to the simultaneous localization and mapping problem at semistructured environments using acoustic images acquired by forward-looking sonars. The images are segmented by an adaptative approach based on the acoustic beams analysis. A pose-invariant topological graph is build to represent the relationship between image features. The loop closure detection is achieved using a graph comparison. The approach is evaluated in a real environment at a marina. The results reveal all loop closures of the data set are detected with a high precision and present an invariant to image rotation.