Exploiting Heterogeneity in Robotic Networks

  • Nicola BezzoEmail author
  • R. Andres Cortez
  • Rafael Fierro
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 57)


In this chapter we consider the problem of coordinating robotic systems with different dynamics, sensing and vision capabilities, to achieve a unisonmission goal. An approach that makes use of a heterogeneous team of agents has several advantages when cost, integration of capabilities, or possible large search areas need to be investigated. A heterogeneous team allows for the robots to become “specialized” in their abilities and therefore accomplish sub-goals more efficiently which in turn makes the overall mission more efficient. We first propose a prioritized search algorithm combined with communication constraints to provide a decentralized prioritized sensing control algorithm for a heterogenous sensor network that maintains network connectivity. By specifying particular edge weights in the proximity graph, we provide a technique for biasing particular connections within the heterogenous sensor network. Then in the second part of the chapter we show a hierarchical approach to optimally allocate the tasks of a mission to specific agents. We develop a decentralized algorithm based on artificial physics and potential functions to guide the heterogeneous robotic network in the environment while maintaining connectivity constraints. Simulations and an experimental result are provided to show the applicability of the proposed frameworks.


Minimum Span Tree Mobile Agent Sensor Agent Mobile Router Communication Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Nicola Bezzo
    • 1
    Email author
  • R. Andres Cortez
    • 2
  • Rafael Fierro
    • 1
  1. 1.Department of Electrical & Computer EngineeringUniversity of New MexicoAlbuquerqueUSA
  2. 2.Los Alamos National LaboratoryLos AlamosUSA

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