Abstract
Unmanned surface vehicles (USVs) require robust situational awareness to navigate safely in complex maritime environments. A critical element of this is to identify the free navigable space around the USV. Free water regions can be derived from water segmentation in the image. However, these segmented regions must be transformed into a bird's eye view (BEV) representation to be utilized effectively in motion planning. This paper proposes a novel approach to estimate free navigable space in a BEV format by integrating a stereo camera and light detection and ranging (LiDAR). The proposed method uses water segmentation to delineate the water surface and represents the closest obstacles in the USV line of sight using vertical planar rectangles known as Stixels. The depth of these Stixels is derived from LiDAR data, ensuring precise positioning in space. The effectiveness of the approach is demonstrated through experiments conducted on real-world data collected from the milliAmpere 2 (MA2) autonomous ferry prototype in Trondheim, Norway. Qualitative evaluations focusing on accuracy and temporal consistency confirm its ability to reliably detect free navigable areas in complex maritime environments.