Challenges in Sensing, Communication, Coordination

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Revision as of 10:54, 10 July 2013 by Wilfried (talk | contribs) (What are the best suitable sensors, communication modules for small-scale UAVs? What is available?)
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Group 1

What are the main challenges?

  • moving decisions on board
  • implicit communication/ without medium
  • local communication
  • how to control / monitor the distributed process "there is a human in the loop"

Group 2

Group 3

What are the main challenges?

  • limited payload
  • processing power
  • data fusion
  • (self-)localization
  • coordination, synchronization of sensing
  • communication (range, loss)
  • collision avoidance
    • should work in worst case scenario (multiple UAVs, obstacles, communication outage)
  • robustness, handling of every possible situation
  • must be fail-operational to maintain safe state (situation-dependent)
  • optimizing the number of flying robots
  • find simple rules to create desired emergent behavior

What are the best suitable sensors, communication modules for small-scale UAVs? What is available?

  • sensors (should be light, low energy-consuming, low signal processing effort)
    • cameras
    • ultrasonic (for indoor, needs to be de-synchronized
    • infrared
    • contactsensors
    • LIDAR
    • IMU
    • GPS
    • wind sensor
    • barometric height sensor
    • sensing earth magnetic field
    • new integrated sensor modules (IMU, camera, processing unit)
  • communication modules
    • radio, e.g., X-Bees
    • IR
    • remote control module (for legal reasons)

ability for multi-hop/mesh networks

Is a UAV swarm feasible? What are the limitations?

depends on scenario, loosly coordinated UAVs flying over a field is possible, cooperatively lifting payload is difficult

  • cost
  • coordination
  • precision in localization
    • error progagation

How do we coordinate the UAVs to achieve team behavior?

  • central coordination
    • simple UAVs
    • communication
    • complexity, scalability
  • decentralized coordination
    • achieving optimal behavior
    • testing the system
    • designing the self-organizing algorithm
    • controllability
  • mixture of both
    • high-level goal done by centralized planning
    • local control for collision avoidance, etc.