The topology of the mobile sensor network is
subject to change with respect to different environments and task specifications.
One of the objectives for a mobile sensor network is to reconfigure the robot position
and maximize sensing capabilities in both constrained and unconstrained areas.
Area coverage and sensor deployment problems have been discussed in a variety of
static sensor networks, such as [8], [29]. However, only limited work has been published
on sensor deployment approaches for coordinated area coverage problems of
mobile sensor networks [10], [22]. This chapter suggests a distributed graph model
for dynamic coverage in a mobile sensor network. The graph model defines the geographical
relationship using Delaunay triangulation where the motion of a robot
is only related to its immediate one-hop neighbors and its environment. Based on
this distributed model, virtual potential field method [23], [25] is combined with the
Delaunay triangulation to develop the distributed autonomous deployment algorithm
for a multiple robots system. The algorithms are proven to be globally convergent
Chapter 3 A Scalable Graph Model and Coordination Algorithms 67
Fig. 1. In a mobile sensor network, each mobile robot is equipped with sensing, communication,
computation capabilities for a wireless mobile sensor network.
and robust to robot failures. The algorithms are extended to the tracking control of
nonholonomic robot systems.
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