Seabed mapping for deep-sea mining vehicles based on forward-looking sonar.

The deep-sea mining vehicle is one of the key equipment for deep-sea mining system, which needs to complete tasks such as traveling on the seabed, ore crushing, ore collection, and ore transportation. During the operation of deep-sea mining vehicles, real-time mapping of the surrounding terrain environment is a necessary guarantee for safety. Forward-looking sonars can perform real-time imaging of underwater environments without being affected by water turbidity, which has been gradually used in underwater environment exploration. In this study, a novel seabed terrain mapping algorithm based on occupancy-elevation grid map for deep-sea mining vehicles, which uses a wide aperture forward-looking imaging sonar is proposed. This paper proposes an inverse sensor model for forward-looking sonar, which can map pixels in the image to the occupied probability and elevation information corresponding to the real space, and use it to generate the occupancy-elevation grid map. Then, a local occupancy-elevation grid map can be constructed as a submap with the inverse sensor model and position information from sonar odometer or other sensors. And the poses of different local submaps are optimized based on factor graph to generate the global occupancy-elevation grid map. The proposed mapping algorithm is validated by both simulation experiments and real data from forward-looking sonar during sea trials. • Proposing an inverse sensor model of the forward-looking sonar to estimate the occupied probability and elevation. • Using 2-D probabilistic space carving to reduce the redundant impact of uncertainty on obstacle areas in sonar images. • Both the simulation and the dataset from sea trials proved that the proposed method can generate a reliable occupancy-elevation grid map successfully. [ABSTRACT FROM AUTHOR]