According to the traffic-rules at sea, all vessels shall at all times maintain a proper lookout by sight and other means. For autonomous ships, this poses a challenge because human vision is a highly refined instrument, having evolved over hundreds of millions of years, whose capabilities are unlikely to be surpassed by artfificial vision. Nevertheless, autonomous navigation systems can offer several advantages that surpass the capabilities of a human operator, such as persistent attention, fusion of vision with active sensors such as radar or lidar, and utmost precision in tracking, navigation and motion control.
To strengthen the utility of computer vision in maritime surface autonomy, the Autosight project will focus on stereo vision. The key principle is that distance can be estimated by comparing how the same scene appears in two cameras placed slightly apart. For human eyes, this baseline distance is around 6 cm, which is sufficient to provide a spatial sense in a small room. For an autonomous vessel, much larger baselines are possible, sufficiently to provide meaningful distance estimation within a harbor environment.
Thus, the Autosight project will investigate what artificial stereo vision can offer in near-shore operations for maritime surface autonomy. This is both as a tool for estimating where the autonomous vessel is relative to its surrounds, and to detect and track other vessels in its vicinity.
The project will establish knowledge about how stereo vision can be used to enable precise and safe operations for autonomous surface vessels in the close vicinity of the shore and other vessels, such as during docking operations of an autonomous ferry. Building upon recent breakthroughs of maritime autonomy and inspired by the advances in vision-based automotive autonomy, the project will critically compare and combine solutions based on both probabilistic models and machine learning. The project will develop tailor-made solutions to localization and extended object tracking in the harbor environment and demonstrate how these solutions can be used to strengthen the safety of an autonomous ferry.