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Experimental Evaluation of Approach Behavior for Autonomous Surface Vehicles

[+] Author Affiliations
Ivan R. Bertaska, Jose Alvarez, Armando Sinisterra, Karl von Ellenrieder, Manhar Dhanak

Florida Atlantic University, Dania Beach, FL

Brual Shah, Petr Švec, Satyandra K. Gupta

University of Maryland, College Park, MD

Paper No. DSCC2013-3838, pp. V002T32A003; 9 pages
doi:10.1115/DSCC2013-3838
From:
  • ASME 2013 Dynamic Systems and Control Conference
  • Volume 2: Control, Monitoring, and Energy Harvesting of Vibratory Systems; Cooperative and Networked Control; Delay Systems; Dynamical Modeling and Diagnostics in Biomedical Systems; Estimation and Id of Energy Systems; Fault Detection; Flow and Thermal Systems; Haptics and Hand Motion; Human Assistive Systems and Wearable Robots; Instrumentation and Characterization in Bio-Systems; Intelligent Transportation Systems; Linear Systems and Robust Control; Marine Vehicles; Nonholonomic Systems
  • Palo Alto, California, USA, October 21–23, 2013
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5613-0
  • Copyright © 2013 by ASME

abstract

This article presents an experimental assessment of an Unmanned Surface Vehicle (USV) executing an approach behavior to several stationary targets in an obstacle field. A lattice-based trajectory planner is implemented with a priori knowledge of the vehicle characteristics. In parallel, a low-level controller is developed for the vehicle using a proportional control law. These systems are integrated on the USV control system using the Lightweight Communications and Marshalling (LCM) message passing system. Filtered vehicle-state information from onboard sensors is passed to the planner, which returns a least-cost, dynamically feasible trajectory for achieving the ascertained goal. The system was tested in a 750 m by 150 m area of the US Intracoastal Waterway in South Florida in the presence of wind and wave disturbances to characterize its effectiveness in a real-world scenario. The vehicle was able to replicate behavior predicted in simulations when navigating around obstacles. The approach distance to each target was favorably lower than the user-defined limit. Owing to the fact that the USV uses differential thrust for steering, the vehicle tracked the planned trajectories better at lower speeds.

Copyright © 2013 by ASME
Topics: Vehicles

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