Bounded Cost Path Planning for Underwater Vehicles Assisted by a Time-Invariant Partitioned Flow Field Model
Abstract
A bounded cost path planning method is developed for underwater vehicles assisted by a data-driven flow modeling method. The modeled flow field is partitioned as a set of cells of piece-wise constant flow speed. A flow partition algorithm and a parameter estimation algorithm are proposed to learn the flow field structure and parameters with justified convergence. A bounded cost path planning algorithm is developed taking advantage of the partitioned flow model. An extended potential search method is proposed to determine the sequence of partitions that the optimal path crosses. The optimal path within each partition is then determined by solving a constrained optimization problem. Theoretical justification is provided for the proposed extended potential search method generating the optimal solution. The path planned has the highest probability to satisfy the bounded cost constraint. The performance of the algorithms is demonstrated with experimental and simulation results, which show that the proposed method is more computationally efficient than some of the existing methods.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jul 14, 2021
- Source ID
- 10.3389/frobt.2021.575267
Entities
People
- Catherine R. Edwards
- Fumin Zhang
- Haomin Zhou
- Mengxue Hou
- Sungjin Cho
Organizations
- Air Force Office of Scientific Research
- National Oceanic and Atmospheric Administration
- National Science Foundation
- Office of Naval Research
- United States Naval Research Laboratory