A
number of mobile sensor deployment algorithms have been proposed, such as the incremental
deployment approach [22], potential field approach [23], [38], constrained
coverage [34], and Voronoi based approach with known distributions [14]. A reactive
approach discusses the deployment of mobile sensors in response to dynamic
events [10]. A control strategy for mobile sensor networks to track sensing gradient
to is discussed in [30]. Among others, mobile sensor networks have found applications
in exploration [3] and network maintenance [13], [12]. On the interaction
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66 Jindong Tan
between sensor networks and mobile robots, robot task allocation and navigation
have recently been discussed [5], [4], [11], [26].
A mobile sensor network is simultaneously a multi-robot system. Based on the
vision that multiple robots have the potential to perform a task faster, and more effi-
ciently than a single robot [32], cooperation and formation control of multiple robots
has been emerging as an important research area [20], [24], [32]. Robot control structures
for cooperation of multiple robots, such as the subsumption structure [7], reactive
control and hybrid control [9], and behavior-based control [2], [28] have been
proposed in the literature. Behavior based robotics [2] coordinates multiple robots
based on a collection of behaviors, which are processes or control laws that achieve
and/or maintain goals. Sophisticated cooperative behavior based on both perception
and symbolic communication, which is common in primates, has also drawn
researchers??™ attention in the cooperation of mobile sensor networks.
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