Networks of Robots and Sensors
Distributed (re)configuartion algorithms for mobile robotic networks with anisotropic sensors
Distributed algorithms for (re)configuring sensors to cover a given
area are important for autonomous multi-robot operations in
application areas such as surveillance and environmental monitoring.
Depending on the assumptions about the choice of the environment, the
sensor models, the coverage metric, and the motion models of sensor
nodes, there are different versions of the problem that have been
formulated and studied. In this work, we consider the problem of
(re)configuring systems equipped with anisotropic sensors (e.g.,
mobile robot with limited field of view cameras) that cover a
polygonal region with polygonal obstacles for detecting interesting
events. We assume that a given probability distribution of the events
over this polygonal region is known. Our model has two key
distinguishing features that are inherently present in covering
problems with anisotropic sensors, but are not addressed adequately in
the literature. First, we allow for the fact that the sensing
performance may not be a monotonically decreasing function of
distance. Second, motivated by scenarios where the sensing performance
not only depends on the resolution of sensing, but also on the
relative orientation between the sensing axis and the event, we assume
that the probability of detection of an event depends on both sensing
parameters and the angle of observation. We present a distributed
gradient-ascent algorithm for (re)configuring the system of mobile
sensors so that the joint probability of detection of events over the
whole region is maximized. Simulation results illustrating the
performance of our algorithms on different systems, namely, mobile
camera networks, mobile acoustic sensor networks, and static
pan-tilt-zoom camera networks are presented.
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B. Hexsel, N. Chakraborty and K. Sycara, `` Distributed Coverage Control for Mobile Anisotropic Sensor Networks '',
Submitted to IEEE Transactions on Systems, Man, and Cybernetics.
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B. Hexsel, N. Chakraborty and K. Sycara, `` Coverage Control for Mobile Anisotropic Sensor Networks '', 2011 IEEE International
Conference on Robotics and Automation, Shanghai, China, May 2011.
Data Collection algorithms for sensor networks
with anisotropic communication capability
In spatially distributed wireless sensor networks, the use of mobile
robotic routers to collect data from the sensor nodes has been
proposed to reduce the communication energy and increase the
network lifetime. In this paper, we study the problem of
constructing a path for a mobile data collecting robot such that the
total data collection cost (i.e., sum of transmission energy by the
sensor nodes and movement energy by the data collecting robot) is
minimized. We assume that the sensor nodes can transmit within a
certain region around their position, which is called the {\em communication
set}. We model the communication set as a convex set (which is a
generalization of the disc transmission models predominantly used in
the literature) to take into account asymmetric transmission systems
(like directional antennas). We derive a necessary condition for the
optimality of a mobile robot tour through the communication sets.
Based on this condition, we design a three-step approach to compute
a local minimum of the optimization problem.
We prove that our solution is guaranteed to be within a constant factor of the global
optimal solution. Our algorithm works for both
$2$-dimensional and $3$-dimensional sensor networks where the sensor
nodes are heterogeneous and can have directional communication
properties. In contrast, existing algorithms for computing data
collecting routes are for planar sensor networks and assume the
communication sets to be discs. We also present simulation results depicting the
performance of our algorithm.
Data collection and aggregation is an important problem in wireless
sensor network (WSN) deployments. In a two-tiered sensor network,
relay nodes with more powerful communication capabilities are placed
to collect the sensor data and transfer to the base station. The
relay node placement (RNP) problem is to find the minimum number of
relay nodes required (and their positions) to transfer the data from
the sensor nodes to the base station. In the extant literature, it
is usually assumed that the region of reliable communication around
a sensor node (i.e., the {\em communication set} of a sensor node)
is a disc. However, the communication set of a sensor node may be
anisotropic, i.e., have different transmission ranges in different
directions. Anisotropicity of the communication sets may be because
of the environment within which the WSN is operating (e.g.,
underwater networks with acoustic communication) and/or because the
communication antenna may be directional. In this paper, we design
a two-step algorithm for the RNP problem where the sensor nodes may
have heterogeneous anisotropic communication sets. We model the
communication sets as convex sets, which is a generalization over
the current disc communication models. In the first step, we give an
approximation algorithm for computing the minimum number of relay
nodes that is within a factor of $1 + \log(q)$ of the optimal
solution. The running time of the algorithm is polynomial in the
number of sensor nodes. Note that, even for unit disc communication
model, computing the minimum number of relay nodes is NP-complete
(the problem is equivalent to a geometric set cover problem). In the
second step, we compute the positions of the relay nodes by solving
a collection of convex optimization (or feasibility) problems. In
contrast to most of the literature that considers only planar sensor
networks, our algorithm works both for two-dimensional ($2D$) and
three-dimensional ($3D$) sensor networks. To demonstrate the
performance of our algorithm, we provide simulation results on
randomly generated networks for $2D$ and $3D$ sensor networks.
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N. Chakraborty, J. Goerner, and K. Sycara, `` Cost-Effective Relay Node Placement in Two-tiered
Sensor Networks with Heterogeneous Communication Sets '', Submitted to IEEE Transactions on
Automation Sciences and Engineering.
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J. Goerner, N. Chakraborty, and K. Sycara, `` Energy Efficient Data Collection with Mobile Robots
in Heterogeneous Sensor Networks '', 2013 IEEE International Conference on Robotics
and Automation (IEEE ICRA 2013) , Karlsruhe, Germany, May 2013.
(Re)Configuration algorithms for mobile robotic
networks
Mobile robotic networks that also serve as a communication backbone
needs to be connected to perform its function usefully. However robot
failure may occur and the network may become disconnected. The
functioning robots in the network should have the capability to
determine that the network has become disconnected and take corrective
actions, i.e., adjust their positions to ensure that the network gets
connected again. Thus, the robots should have the capability for
self-healing. In this paper, under the assumptions of disc
communication model, we present a distributed incremental algorithm
for a robotic network to self-heal. Since the adjustment of the
network is inherently local for a robot, it is desirable for the
algorithm to have the property that only robots that need to adjust
their positions, participate in the computation. Thus the algorithm is
incremental in the sense that it involves robots only when they may
need to adjust their positions. We present simulation results
demonstrating our algorithm.
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