PhD Proposal by Jean-Guillaume D.S. Durand

Event Details
  • Date/Time:
    • Friday May 13, 2016
      12:00 pm - 2:00 pm
  • Location: Weber Space Science and Technology Building (SST-II): Collaborative Visualization Environment (CoVE)
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Summary Sentence: A METHODOLOGY TO ACHIEVE MICROSCOPIC/MACROSCOPIC CONFIGURATION TRADEOFFS IN MULTI-ROBOT COOPERATIVE SYSTEMS DESIGN

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Ph.D. Thesis Proposal

 

By

 

Jean-Guillaume D.S. Durand

(Advisor: Prof. Dimitri N. Mavris)

12:00 PM, Friday, May 13, 2016

Weber Space Science and Technology Building (SST-II)

Collaborative Visualization Environment (CoVE)

 

A METHODOLOGY TO ACHIEVE MICROSCOPIC/MACROSCOPIC CONFIGURATION TRADEOFFS IN MULTI-ROBOT COOPERATIVE SYSTEMS DESIGN

 

 

Abstract:

The exponential growth experienced by the robotics sector over the past decade has fostered the proliferation of new architectures. Optimized for specific missions, these platforms are in most cases limited by their embarked computational power and a lack of full situational awareness. More robust, flexible, scalable, and inspired by nature, group robotics represent an interesting approach to overcome some limitations of these single agents and take advantage of the heterogeneity of the current robotics fleet. Their essence lies in accomplishing more complex synergistic behaviors through diversity, simple rules and local interactions. However, the design of robotic groups is complex as decision-makers have to optimize the group operation as well as the performance of each individual unit, for the group performance. In particular, key questions arise to know whether resources should be allocated on the characteristics of the group, or on the individual capabilities of its agents in order to meet the established requirements.

 

Current methods of swarm engineering tend to perform sequential optimization of the microscopic level (the agents) and then the macroscopic level (the group) which results in suboptimal architectures. In this context, efficiently comparing two different groups or quantifying the superiority of a group versus a single robot design can reveal impossible. Same goes of the determination of an optimal architecture for a given mission. With a special emphasis on aerial vehicles, the present research proposes to establish a methodology to achieve microscopic/macroscopic configuration tradeoffs in the design of multi-robot cooperative systems. A novel multi-level multi-architecture morphological approach is introduced for design space exploration and a mesoscopic level simulation-based design method is used to bridge the gap between microscopic and macroscopic levels. The capabilities of this method are demonstrated through a heterogeneous mapping/imaging testbed application.

 

Committee Members:

Prof. Dimitri N. Mavris

Prof. Daniel P. Schrage

Dr. Eric Feron

 

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Phd proposal
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  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: May 11, 2016 - 6:47am
  • Last Updated: Oct 7, 2016 - 10:17pm