Towards Low-Cost Real-Time Seafloor Featureless Visual Odometry

Navigating the undersea environment is a challenging task for modern visual odometry algorithms due to poor visibility and a lack of distinct points for feature-based match-making. This effort aims to increase the navigation capability of undersea vehicles via the adoption of a more robust, featureless image registration algorithm for visual odometry. Featureless image registration utilizes the frequency domain to match images based on their cross-power spectrum and therefore does not re-quire distinct feature points. As such, this method shows reliable registration in environments with varying texture, lighting, and contrast. The proposed algorithm has a consistent computational cost capable of real-time use on low-cost systems such as the Raspberry Pi 4B + microcomputer. In addition, low-cost camera technologies were also utilized to demonstrate their ability to reduce barriers to entry for autonomous ocean research. The results demonstrated satisfactory velocity estimation and reliable altitude measurements utilizing calibrated stereo cameras. The proposed method builds off a number of works encouraging the use of featureless-based image registration algorithms in the undersea environment as opposed to more traditional algorithms and opens up avenues for future work in enhanced localization capabilities for undersea vehicles.