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

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.