A hierarchical control and obstacle avoidance system for Unmanned Sea Surface Vehicles

P. Krishnamurthy, F. Khorrami

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, the development of a hierarchical control, path planning, and obstacle avoidance system for autonomous operation of Unmanned Sea Surface Vehicles (USSVs) in uncertain cluttered environments (e.g., littoral environments) is described. The system is designed with a modular structure incorporating a robust inner-loop controller and a hierarchical combination of wide-area, intermediate-area, and local-area planning and obstacle avoidance algorithms. The performance of the proposed system has been demonstrated through Hardware-In-The-Loop (HITL) and experimental tests. The HITL simulation platform incorporates detailed dynamics of the USSV including hydrodynamic effects as well as emulation of sensors and instrumentation onboard the USSV including Radar. The HITL platform can simultaneously simulate multiple USSVs and passive obstacles and provides the computer which runs the controls and obstacle avoidance algorithms with the exact environment which it sees when operating in the experimental USSV testbed.

Original languageEnglish (US)
Title of host publication2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2070-2075
Number of pages6
ISBN (Print)9781612848006
DOIs
StatePublished - 2011
Event2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 - Orlando, FL, United States
Duration: Dec 12 2011Dec 15 2011

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Other

Other2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
Country/TerritoryUnited States
CityOrlando, FL
Period12/12/1112/15/11

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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