PhD defense

The PhD thesis was successfully defended the 23th November. The details are given below. 



Date: 23th November 2012


Place:  Salle Mont Blanc of Gipsa-Lab, Grenoble, France


Title:  Agreement strategies for multi-robot systems


Directors:  Carlos Canudas de Wit

                                Alexandre Seuret



Sandra Hirche    TUM, Munich, Germany
Christopher Edwards    University of Leicester, Leicester, United Kingdom
Antonio M. Santos Pascoal      IST, Lisboa, Portugal
Dimos V. Dimarogonas    KTH, Stockholm, Sweden
Mazen Alamir    GIPSA-Lab/CNRS, Grenoble, France
Alexandre Seuret  

   GIPSA-Lab/CNRS, Grenoble, France


Abstract:  The idea of deploying formations of relatively unsophisticated autonomous robots to accomplish complicated tasks has roots in the early works studying the flocking and foraging behaviors among birds. The main question was how one can mimic different behaviors witnessed in populations of birds, animals, insects, etc. among a population of artificial agents. The emerging use of large-scale multi-agent and multi-vehicle systems in various modern applications has recently raised the need for the design of control laws to perform challenging spatially-distributed tasks such as search and recovery operations, exploration, surveillance, environmental monitoring or pollution detection and estimation among many others.


This dissertation focuses on distributed agreement strategies to control a set of mobile robots. A significant part of the thesis deals with consensus algorithms of arbitrary linear heterogeneous agents, representing, for example, different models or generations of robots. Motivated by the fact that only a few works consider heterogeneous cases of the synchronization problem, we proposed a control strategy based on consensus algorithm which is decoupled from the original system. The new algorithm offers the major advantage to separate the stability analysis of each agent and the convergence analysis of the distributed consensus algorithm.


On a second set of works, we focus on consensus algorithm's convergence rate and more particularly, in accelerating it.  Using the stabilizing delay principle, we added a state sampled component to the control law that can be seen as an artificial way to manipulate graph’s algebraic connectivity.


Finally, we designed and analyzed an algorithm for compact deployment of agents  In our approach, the desired formation is specified entirely by angles formed by agents within the formation. We proposed a completely distributed algorithm, only based on relative positions that allow swarm's self-organization, while improving the graphs'  connectedness.