Development of an Underwater Vision Sensor for 3D Reef Mapping

Coral reef health is an indicator of global climate change and coral reefs themselves are important for sheltering fish and other aquatic life. Monitoring reefs is a time-consuming and potentially dangerous task and as a consequence autonomous robotic mapping and surveillance is desired. This paper describes an underwater vision-based sensor to aid in this task. Underwater environments present many challenges for vision-based sensors and robotic vehicles. Lighting is highly variable, optical snow/particulate matter can confound traditional noise models, the environment lacks visual structure, and limited communication between autonomous agents including divers and surface support exacerbates the potentially dangerous environment. We describe experiments with our multi-camera stereo reconstruction algorithm geared towards coral reef monitoring. The sensor is used to estimate volumetric scene structure while simultaneously estimating sensor ego-motion. Preliminary field trials indicate the utility of the sensor for 3D reef monitoring and results of land-based evaluation of the sensor are shown to evaluate the accuracy of the system