Autonomous underwater vehicle trajectory design coupled with predictive ocean models: A case study

Ryan N. Smith, Arvind Pereira, Yi Chao, Peggy P. Li, David A. Caron, Burton H. Jones, Gaurav S. Sukhatme

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

50 Scopus citations

Abstract

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 evolving ocean feature utilizing ocean model predictions. This builds on previous work in this area by incorporating the predicted current velocities into the path planning to assist in solving the 3-D motion planning problem of steering an AUV between two selected locations. We present simulation results for tracking a fresh water plume by use of our algorithm. Additionally, we present experimental results from field trials that test the skill of the model used as well as the incorporation of the model predictions into an AUV trajectory planner. These results indicate a modest, but measurable, improvement in surfacing error when the model predictions are incorporated into the planner.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Robotics and Automation, ICRA 2010
Pages4770-4777
Number of pages8
DOIs
StatePublished - Aug 26 2010
Event2010 IEEE International Conference on Robotics and Automation, ICRA 2010 - Anchorage, AK, United States
Duration: May 3 2010May 7 2010

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Other

Other2010 IEEE International Conference on Robotics and Automation, ICRA 2010
CountryUnited States
CityAnchorage, AK
Period05/3/1005/7/10

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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