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Invited talks:

Graph-based control of heterogeneous robot networks
Magnus Egerstedt Georgia Institute of Technology, GA, USA
 
Arguably, the overarching scientific challenge facing the area of networked robot systems is that of going from local rules to global behaviors in a predefined and stable manner. In particular, issues stemming from the network topology imply that not only must the individual agents satisfy some performance constraints in terms of their geometry, but also in terms of the combinatorial description of the (dynamic) network. Moreover, a multi-agent robotic network is only useful inasmuch as the agents can be redeployed and reprogrammed with relative ease, and we address these two issues (local interactions and programmability) from a controllability point-of-view. In particular, the problem of driving a collection of mobile robots to a given target destination is studied, and sufficient conditions are given for this to be possible, based on novel tools from algebraic graph theory.
 

A multi-level modeling methodology for swarm robotic systems
Alcherio Martinoli Ecole Polytechnique Fédérale de Lausanne, Switzerland
 

In this talk, I will first introduce the characteristic features of Swarm Robotics, a new, promising sub-area of distributed robotics dealing with large numbers of relatively simple robotic nodes. I will then illustrate with concrete examples how the application of both bio-inspired principles and more traditional model-based approaches to artificial, distributed, embedded platforms such as swarm robotic systems is not straightforward and shows several limitations. As potential answer to such limitations, I will then present a methodology based on multiple levels of abstraction we have developed to evaluate, control, and optimize the performances of swarm robotic systems. I will support the discussion with concrete case studies mainly concerned with non-spatial performance metrics, both in distributed sensing and manipulation. I will conclude the seminar by discussing advantages and limitations of the current methodology, and show a number of recent efforts aiming at relaxing the underlying assumptions and increasing its generality.