PhD Defense by Daniel Pickem

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  • Date/Time:
    • Wednesday July 29, 2015 - Thursday July 30, 2015
      10:00 am - 11:59 am
  • Location: TSRB 530
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Summary Sentence: Self-Reconfigurable Multi-Robot Systems

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Ph.D. Thesis Proposal Announcement

 Title: Self-Reconfigurable Multi-Robot Systems

 Daniel PickemRobotics Ph.D. StudentSchool of Electrical and Computer EngineeringCollege of EngineeringGeorgia Institute of Technology

 Date: July 29, 2015 (Wednesday)Time: 10am - 12pm ESTLocation: TSRB 530

 Committee:Dr. Justin Romberg, School of Electrical and Computer Engineering, Georgia TechDr. Martha A. Grover, School of Chemical and Biomolecular Engineering, Georgia TechDr. Jun Ueda, School of Mechanical Engineering, Georgia TechDr. Jeff S. Shamma, School of Electrical and Computer Engineering, Georgia TechDr. Magnus Egerstedt, School of Electrical and Computer Engineering, Georgia Tech

Abstract:Self-reconfigurable robot systems are comprised of individual modules which are able to connect to and disconnect from one another to form larger structures. These systems therefore have the ability to change their morphology and functionality and thus adapt to changing tasks and environments. 
Optimally reconfiguring such systems is NP-hard, which makes centralized solutions unsuitable for solving the self-reconfiguration problem for large systems. As a result, self-reconfiguration approaches aim at approximating optimal solutions. Nonetheless, even for approximate solutions, centralized methods scale poorly in the number of modules. Therefore, the objective of this proposal is the development of decentralized methods for the self-reconfiguration of modular robotic systems. Building on completeness results of the centralized algorithms in this proposal, decentralized solution methods are developed that guarantee convergence to global optima, i.e. reconfigure initial into target configurations.

 A game theoretic approach lays the theoretical foundation of a novel potential game-based formulation of the self-reconfiguration problem. Stochastic convergence guarantees are provided for a large class of utility functions used by purely self-interested agents. This flexibility in the choice of utility functions makes the presented approach and the underlying theory suitable for a wide array of problems that rely on decentralized local control to guarantee global, emerging properties.

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Phd Defense
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: Jul 13, 2015 - 6:49am
  • Last Updated: Oct 7, 2016 - 10:12pm