Autonomous Underwater Vehicle trajectory design coupled with predictive ocean models: A case study

— Data collection using Autonomous Underwater Vehicles (AUVs) is increasing in importance within the oceanographic research community. Contrary to traditional moored or static platforms, mobile sensors require intelligent planning strategies to maneuver through the ocean. However, the ability to navigate to high-value locations and collect data with specific scientific merit is worth the planning efforts. In this study, we examine the use of ocean model predictions to determine the locations to be visited by an AUV, and aid in planning the trajectory that the vehicle executes during the sampling mission. The objectives are: a) to provide near-real time, in situ measurements to a large-scale ocean model to increase the skill of future predictions, and b) to utilize ocean model predictions as a component in an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. We present an algorithm designed to generate paths for AUVs to track a dynamically evol...

• Type: Journal
• Year: 2010
• Where: ICRA
• Authors: Ryan N. Smith, Arvind Pereira, Yi Chao, Peggy Li, David A. Caron, Burton H. Jones, Gaurav S. Sukhatme
• Keywords: ICRA 2010, Mobile Sensor, Ocean Model Predictions, Planning, Robotics