Sensing and Autonomy for Riverine Vessels
Abstract
The principal goal of this project is to develop the technology and algorithms that will enable an unmanned surface vehicle (USV) to operate fast and autonomously in unknown riverine environments, including tropical rivers. Robust autonomy requires that the USV senses the surface and subsurface environments, discriminates waterways that are navigable from those that are not, indentifies stationary and moving obstacles, including other vessels, and then optimally plans and re-plan a route in real time. Since speed is a vessel s principal defense, all of these tasks must be done as efficiently as possible to ensure successful operation at the greatest possible speed. This project is tightly coordinated with collaborators at the Naval Postgraduate School (NPS) whose work is conducted under a related project. Specific objectives for VT and NPS during 2011 reported herein are: 1. Develop a sparse topological representation for a riverine system suitable for fast planning over very large areas. 2. Development of a generalized sonar mount so that our autonomy and sensing package can be mounted on most riverine vessels. 3. Development of a feedback control architecture that is suitable for the full operating envelope of a riverine vessel, including sternward motion. 4. Development of a method for computing dynamically feasible trajectories that include sternward motion. We seek to develop a sensing and autonomy package that can be deployed on a variety of small vessels. Thus our activities are focused on the development of sensing strategies, and guidance and control algorithms, rather than on the development of a specific USV platform. Our goal is to operate quickly in large areas for which existing maps are inaccurate. The principal result of this project will be a set of algorithms and best-practice tools for robust autonomous surface vehicle operations in dynamic and partially mapped riverine systems.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 2011
- Accession Number
- ADA557264
Entities
People
- Craig A Woolsey
- Daniel J. Stilwell
Organizations
- Virginia Tech