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International Conference on Complex Systems (ICCS2006)

Distributed resource exploitation for autonomous mobile sensor agents in dynamic environments

Sarjoun Doumit
University of Cincinnati

Ali Minai
University of Cincinnati


     Full text: PDF
     Last modified: August 16, 2006

Abstract
This paper studies the distributed resource exploitation problem (DREP) where
many resources distributed are across an unknown environment, and several agents
move around in it with the goal to exploit/visit the resources. A resource may
be anything that can be harvested/sensed/acted upon by an agent when the agent
visits that resource's physical location. An agent is mobile and autonomous
sensory entity (SA) that has the capability of sensing a resource's attribute
and therefore determining the exploitatory gain factor or profitability when
this resource is visited. This type of problem can be seen as a combination of
two well-known problems: the Dynamic Travelling Salesman Problem (DTSP) and the
Vehicle Routing Problem (VRP). But the DREP differs in a principal way from
these two as we consider the environment and the resources to be dynamic. In the
DTSP we have a single agent that needs to visit many fixed cities that have
costs associated to their pairwise links, so it is an optimization of paths on a
static graph. In VRP on the other hand, we have a number of vehicles with
uniform capacity, a common depot, and several stationary customers scattered
around an environment, so the goal is to find the set of routes with overall
minimum route cost to service all the customers. In our problem, we have
multiple SAs deployed in an unknown environment with multiple dynamic resources
each with a dynamically varying value. The goal of the SAs is to adapt their
paths collaboratively to the dynamics of the resources in order to maximize the
general profitability of the system. Applications of this nature range from
exploratory missions such as those of rovers on planets to surveillance,
monitoring, resupply and survival in hazardous environments.




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