Development and experimental evaluation of visual-acoustic navigation for safe maneuvering of unmanned surface vehicles in harbor and waterway areas

Abstract

Ship maneuvering in narrow harbor environments requires accurate navigation data to operate safely. Since Global Navigation Satellite Systems (GNSS) can be unreliable and inaccurate in such environments, other aiding techniques should be used for increased redundancy and reliability. To this end, we present a GNSS-free sensor suite consisting of visual, acoustic, and inertial sensors that can be used to navigate small vehicles in a harbor environment. The proposed method is aided by two navigation systems: a doppler velocity log (DVL) for low-drift velocity aiding and a visual fiducial system to estimate the drift-free position and attitude of a camera onboard the vehicle with respect to easily identifiable tags at the dockside. The visual and acoustic measurements are fused with inertial data using an error-state Kalman filter for robust state estimation. To benchmark the performance, we employ an unmanned surface vehicle equipped with a dual-antenna real-time kinematic GNSS receiver for accurate positioning and heading. The benefits of supplementing landmark-based navigation with acoustic measurements are demonstrated by conducting adverse scenarios that include noisy measurements and sensor dropouts in the harbor environment. As a result, the proposed visual-acoustic system can supplement satellite-based navigation systems for safety-critical harbor maneuvering.