Implementation of a Hydrodynamic Model-Based Navigation System for a Low-Cost AUV Fleet

• Main Authors: Randeni P., Supun A. T. (Author), Rypkema, Nicholas R. (Author), Fischell, Erin M. (Author), Forrest, Alexander L. (Author), Benjamin, Michael R. (Author), Schmidt, Henrik (Author)
• Other Authors: Massachusetts Institute of Technology. Laboratory for Autonomous Marine Sensing Systems (Contributor), Massachusetts Institute of Technology. Department of Civil and Environmental Engineering (Contributor), Woods Hole Oceanographic Institution (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE), 2021-11-09T17:49:32Z.
• Subjects: Article
• Online Access: Get fulltext

 © 2018 IEEE. This work implements a hydrodynamic model-based localization and navigation system for low-cost autonomous underwater vehicles (AUVs) that are limited to a micro-electro mechanical system (MEMS) inertial measurement unit (IMU). The hydrodynamic model of this work is uniquely developed to directly determine the linear velocities of the vehicle using the measured vehicle angular rates and propeller speed as inputs. The proposed system was tested in the field using a fleet of low-cost Bluefin SandShark AUVs. Implementation of the model-based localization system and fusing of the solution into the vehicle navigation loop was conducted using backseat computers of the AUV fleet that run mission orientated operating suite -interval programming (MOOS-IvP). With the model-based navigation system, the maximum localization error (i.e., in comparison to a long baseline (LBL) based ground-truth position) was limited to 15 m and 30 m for two 650-second and 1070-second long missions. Extrapolation of the position drift shows that the model-based localization system is able to limit the position uncertainty to less than 100 m by the end of hour-long mission; whereas, the drift in the default IMU-based localization solution was over 1 km per hour. This is a considerable improvement by only using a MEMS IMU that generally costs less than 100. Furthermore, this work is a step towards generalizing and automating the process of hydrodynamic modeling, model parameter estimation and data fusion (i.e., fusing the localization solution with those from other available aiding sensors and feeding to the navigation loop) so that a model-based localization system can be implemented in any AUV that has backseat computing capability. Index Terms-Autonomous underwater vehicles, model-based localization, hydrodynamic models, system identification, underwater navigation