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Design Innovation Paper

Online Task Decomposition for Collaborative Surveillance of Marine Environment by a Team of Unmanned Surface Vehicles

[+] Author and Article Information
Shaurya Shriyam

Department of Aerospace & Mechanical Engineering, University of Southern California, Los Angeles, CA USA
shauryashri@gmail.com

Brual Shah

Department of Aerospace & Mechanical Engineering, University of Southern California, Los Angeles, CA USA
bcs_862@usc.edu

Satyandra K. Gupta

Department of Aerospace & Mechanical Engineering, University of Southern California, Los Angeles, CA USA
guptask@usc.edu

1Corresponding author.

ASME doi:10.1115/1.4038974 History: Received September 26, 2017; Revised December 14, 2017

Abstract

This paper introduces an approach for decomposing exploration tasks among multiple Unmanned Surface Vehicles (USVs) in congested regions. In order to ensure effective distribution of the workload, the algorithm has to consider the effects of the environmental constraints on the USVs. The performance of the USV is influenced by the surface currents, risk of collision with the civilian traffic, and varying depths due to tides, and weather. The team of USVs needs to explore a certain region of the harbor and we need to develop an algorithm to decompose the region of interest into multiple sub-regions. The algorithm overlays a 2D grid upon a given map to convert it to an occupancy grid, and then proceeds to partition the region of interest among the multiple USVs assigned to explore the region. During partitioning, the rate at which each USV is able to travel varies with the location. The objective is to minimize the time taken for the last USV to finish exploring the assigned area. We use the particle swarm optimization (PSO) method to compute the optimal region partitions. The method is verified by running simulations in different test environments. We also analyze the performance of the developed method in environments where velocity restrictions are not known in advance.

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