Regional target surveillance with cooperative robots using APFs

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Title: Regional target surveillance with cooperative robots using APFs
Author: LaRocque, Jessica
Abstract: Target surveillance in a bounded environment has been a growing focus in the past few years, particularly with recent world events prompting the need for environmental monitoring using automated surveillance. Scenarios exist where the goal is to be able to track targets within a certain distance and yet maintain a proper distribution of the surveillance units to provide field coverage. Previous works in this area using mobile robots as the surveillance units have made assumptions of a global awareness capability provided by a central controller. Artificial Potential Fields (APFs) have been used in cooperative robots and swarm research for applications such as threat containment and related formation control without as much focus on the surveillance tasks. This thesis aims to extend the use of APFs to the concept of Regional Target Surveillance in a distributed algorithm among cooperative robots, with the utilization of Voronoi cells to aid in coverage control. This investigation proposes a system to utilize only the necessary number of robots with local awareness capability. Each of these robots integrates the use of a centroid force and a target force to provide a balanced coverage and target tracking performance. This is accomplished by implicitly defining three circular regions of responsibility for each robot, namely, the full sensing region, the target tracking region, and the centroid calculation region. The target tracking region is within the full sensing region and encompasses the centroid calculation region. The centroid calculation region is used to define the Voronoi cells and thus the centroid of the responsible field of each robot. By adjusting the relative size of the three regions, the system accomplishes implicit target handoff between robots, and, in turn, provides an overall balance between regional target tracking and environmental coverage for the surveillance goal. Matlab simulation results show that with a proper balance in the tradeoff between the tracking and coverage performance, the algorithm is scalable to larger field sizes with a similar robot density, while successfully accomplishing the surveillance tasks.
Record URI: http://hdl.handle.net/1850/12489
Date: 2010-04

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