Accession Number:

ADA558942

Title:

Multiple-Vehicle Resource-Constrained Navigation in the Deep Ocean

Descriptive Note:

Master's thesis

Corporate Author:

MASSACHUSETTS INST OF TECH CAMBRIDGE JOINT PROGRAM IN APPLIED OCEAN SCIENCE AND ENGINEERING

Personal Author(s):

Report Date:

2011-09-01

Pagination or Media Count:

150.0

Abstract:

This thesis discusses sensor management methods for multiple-vehicle fleets of autonomous underwater vehicles, which will allow for more efficient and capable infrastructure in marine science, industry, and naval applications. Navigation for fleets of vehicles in the ocean presents a large challenge, as GPS is not available underwater and dead-reckoning based on inertial or bottom-lock methods can require expensive sensors and suffers from drift. Due to zero drift, acoustic navigation methods are attractive as replacements or supplements to dead-reckoning, and centralized systems such as an Ultra-Short Baseline Sonar USBL allow for small and economical components onboard the individual vehicles. Motivated by subsea equipment delivery we present model-scale proof-of-concept experimental pool tests of a prototype Vertical Glider Robot VGR, a vehicle designed for such a system. Due to fundamental physical limitations of the underwater acoustic channel, a sensor such as the USBL is limited in its ability to track multiple targets at best a small subset of the entire fleet may be observed at once, at a low update rate. Navigation updates are thus a limited resource and must be efficiently allocated amongst the fleet in a manner that balances the exploration versus exploitation tradeoff. The multiple vehicle tracking problem is formulated in the Restless Multi-Armed Bandit structure following the approach of Whittle in 108, and we investigate in detail the Restless Bandit Kalman Filters priority index algorithm given by Le Ny et al. in 71. We compare round-robin and greedy heuristic approaches with the Restless Bandit approach in computational experiments. For the subsea equipment delivery example of homogeneous vehicles with depth-varying parameters, a suboptimal quasi-static approximation of the index algorithm balances low landing error with safety and robustness.

Subject Categories:

  • Cybernetics
  • Underwater and Marine Navigation and Guidance

Distribution Statement:

APPROVED FOR PUBLIC RELEASE