topology control and mobility strategy for uav ad-hoc networks
DESCRIPTION
Joint Joint ERCIM eMobility and MobiSense WorkshopTRANSCRIPT
Joint ERCIM eMobility and MobiSense Workshop
Topology Control and Mobility Strategy for UAV Ad-hoc Networks
Zhongliang Zhao and Torsten BraunUniversität Bern, [email protected], cds.unibe.ch
Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Overview
> Target Application Scenarios> UAV Swarms> Motivation > Related Work
— Boids Flocking— Potential Field— Virtual Springs— Comparison of Approaches
> Topology Control for UAV Ad-hoc Networks
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Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Target Application Scenarios
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Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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UAV Swarms
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UAV Platform
> mikokopter.de > 4 brushless motors, controlled by 4 controllers> FlightControl> NaviControl> MK3Mag (3-axis compass)> GPS module> 3 gyroscopes> 3-axis acceleration sensor> Pressure/height sensor
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Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Motivation I
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> UAVs equipped with wireless mesh nodes form highly mobile ad-hoc network (MANET)
> Connectivity required for live monitoring in areas of interest or other real-time applications
> Example applications— Security— Agricultural/environmental
sensing— Streaming of sports events— Disaster recovery— Communications relaying
Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Motivation II
> Maintaining connectivity in highly mobile MANETS is challenging.
> Needed: MANET topology control mechanism based on swarm control schemes for UAV groups
> Challenges— Application dependent parameters (speed, direction, density)
of UAV swarm— Dynamic wireless channel characteristics— Connectivity versus coverage needed by application— Resource-constrained UAVs
– Mesh nodes with limited processing and communication facilities (bandwidth, transmission range)
– Batteries are usually sufficient for a few 10 minutes.
Santorini, June 8, 2012
Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Related Work
Approaches from distributed agent-based formation control> Boids flocking> Potential field> Virtual Springs
Santorini, June 8, 2012
Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Boids Flocking
Superposition of > Separation
— Collision avoidance> Alignment
— of speed and directions> Cohesion
— Attraction to centroid between neighbours to stay close to them
results in formation building with a common heading and avoiding collisions
Santorini, June 8, 2012
Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Potential Field
> Techniques developed in distributed robotics control
> Attractive and rejective virtual potential fields to/from goals/objects
> Rejective forces between objects decrease with increasing distance
> Attractive forces between objects increase with increasing distance.
Santorini, June 8, 2012
Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Virtual Springs
> Each object, e.g., UAV, forms virtual connection with each neighbour object.
> Resulting forces should be 0 in equilibrium. > Force in each dimension to an object is
— L: Length of spring to neighbour object i— K: constant of spring to neighbour object i— D: distance to neighbour object i— Xi, Yi, Zi: position of neighbour object i
— Xi, Yi, Zi: position of object.
> Completely distributed processing, but neighbour knowledge required.
Santorini, June 8, 2012
Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Comparison of Approaches
Mechanism Pros and Cons Applications
Boids Flocking Cons: mostly for computer animation
Connectivity
Virtual Spring Cons: only distance is utilized, not accurate
Coverage
Potential Field Pros: Both distance and RSSI are used
Coverage and connectivity
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Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Topology Control for UAV Ad-hoc Networks
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> Consideration of wireless channel characteristics, e.g. RSSI measured by wireless receivers, in addition to location information obtained by GPS
> Proposed Approach— Elect swarm leaders that indicate swarm direction and speed— Distributed control of relative movements within UAV swarm
– Define lower / upper bounds for target distance and RSSI– Modify potential field approach by considering RSSI values and GPS
data, e.g.,– Rejective forces for collision avoidance: increasing force for
decreasing distance and for increasing RSSI between 2 UAVs– Attractive forces for maintaining connectivity: increasing force for
increasing distance and for decreasing RSSI between 2 UAVs– Weighting of RSSI and distance to calculate rejective and attractive forces– Use GPS data as backup for lacking channel information or lost
connectivity
Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Rejective/Attractive Forces
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F
distance(RSS)between objects
minimum distance / optimum distance / maximum distancemaximum RSS / optimum RSS / minimum RSS
Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Outlook
> Design and Implementation of — MANET topology control mechanism— Opportunistic multi-channel routing protocol— Applications, e.g., multi-hop relaying, agricultural monitoring
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Torsten Braun: Topology Control and Mobility Strategy for UAV Ad-hoc Networks: A Survey
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Thanks for your attention !
> [email protected] > cds.unibe.ch
Santorini, June 8, 2012