Development and testing of a navigation solution for Autonomous Underwater Vehicles based on stereo vision

Abstract

Autonomous Underwater Vehicles (AUVs) employed for inspection and monitoring applications require a reliable estimate of their navigation status to successfully accomplish the scheduled mission. Considering that they are typically endowed with vision systems to collect images of the surveyed environment, approaches based on Visual Odometry (VO) allow to utilise the optical payload also to perform robot navigation. Despite a large body of prior research, the topic of navigation based on stereo vision is still an open problem in the marine domain. Within this context, this paper proposes an underwater navigation framework utilising a stereo camera as a linear velocity sensor. The purpose is to assess the potentiality of a stereo vision system to indirectly measure the linear velocity of an AUV, and provide this information to the navigation framework of the vehicle. The proposed strategy consists in a visual inertial odometry solution fusing linear velocity estimates, derived from optical information, with attitude and depth measurements to retrieve the robot navigation status. Such linear velocity estimates are computed exploiting a stereo VO algorithm, relying on a 3D-to-2D approach, whose source code is made available online. The developed strategy is evaluated on real underwater datasets acquired during monitoring surveys performed by an AUV equipped with Doppler Velocity Log (DVL), bottom-looking stereo camera, inertial unit, and depth sensor. The results, obtained through a comparison with the DVL taken as benchmark, confirm the approach as feasible and exploitable in underwater inspection and monitoring contexts.