Cooperative Control of Distributed Autonomous Vehicles in Adversarial Environments

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Cooperative Control of Distributed Autonomous
Vehicles in Adversarial Environments

• 2002 MURI Minisymposium
• Ameesh Pandya
• Prof. Greg Pottie

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Overview

• Fault tolerant communication network supporting
  hierarchical distributed communication network.
• Robust network algorithm for highly dynamic
  mobile nodes (say, UAVs).
• Providing minimum communications between mobile
  nodes to minimize the probability of jamming.
• Working closely with Prof. Speyers group to
  develop the communication model according to
  control traffic.

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Wireless Communication Model

• Application Layer
• Transport layer
• IP
• Network
• Link Layer
• MAC Layer
• Radio
• Channel

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Our Concentration

• Application Layer
• Transport layer
• IP
• Network
• Link Layer
• MAC Layer
• Radio
• Channel

Area of Concentration
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QoS Constraints for Control Traffic

• Data Rate for the control traffic 2 Mbps
• This could be considered as the upper bound.
• Achieved by using 2 Mbps modem.
• Latency for control traffic 0 100 ms
• Worst latency is 100ms for control traffic.

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Channel Capacity

• Capacity constraint for the control traffic.
• Channel capacity in terms of received and
  transmitted power, jamming power, spread factor,
  bit rate.
• Goal is to know the reliable transmitting
  distance between the nodes at 2Mbps for the given
  parameters.

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Channel Capacity

• Assumptions
• Isotropic antenna
• Spread spectrum modulation.
• For Low probability of intercept (LPI), Pr/WsN0
  0.1, where Pr is the received power and Ws is
  the band width of spread spectrum signal.

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Channel Capacity

• Shannons Equation
• where, Pr is the received power, W is the channel
  bandwidth.
• For isotropic antenna,
• where Pt is the transmitted power
• Spread factor, f Ws/R, where Ws is the band
  width of the spread spectrum signal and R is the
  information rate in bps.

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Channel Capacity

• If we do not consider broadband jammer, then
• In presence of broadband jammer capacity becomes
• where, is the average jamming power at
  distance r from the receiver
• If we use CDMA, then in presence of jammer for Nu
  simultaneous users, channel capacity is given by
  (assuming identical signal power)

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Simulation Result

• Achievable transmitting distance at 2 Mbps for
  different values of transmitting power.
• Here, the transmitting power is assumed to be 1
  Watt and 2 Watts.
• Assuming available channel bandwidth to be
  100Mbps.
• Simulation carried out with the assumption of
  ideality i.e. no jammer and propagation loss.

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MAC Layer Clustering

• Considering n nodes (UAVs).
• Selecting clusters (cluster heads).
• Each cluster having back bone node.
• Using optimal cluster algorithm.

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Future Objectives

• Developing clustering algorithms for mobile nodes
  in dynamic environment.
• Clustering algorithms
• UAV - UAV
• UAV - UGV
• Obtaining simulation results on the performance
  and robustness of the algorithm.

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Insight

• The solution to the communication network model
  for this particular problem may be very close
  to IPv6.
• Looking into this possibility.