Online Data Summaries For Semantic Mapping And Anomaly Detection With Autonomous Underwater Vehicles

Autonomous underwater vehicle (AUV) operations are inherently bandwidth limited but increasingly data intensive. This leads to large latencies between the capture of image data and the time at which operators are able to make informed decisions using the results of a survey. As AUV endurance and reliability continue to improve, there is a greater need for realtime on-board data processing capabilities. In this paper, we apply online data summary techniques to optical and acoustical imagery collected by AUVs, then show how they can be used to both create low-bandwidth semantic maps and to detect anomalies on the seafloor.