Distributed Control of Robotic NetworksA Mathematical Approach to Motion Coordination Algorithms
Workshop at 2008 IEEE Conference in Decision and ControlDistributed Control of Robotic Networks SpeakersFrancesco Bullo, University of California, Santa Barbara RationaleThe main objective of this workshop is to provide an introduction to the modeling, analysis, and design of robotic networks. The emerging discipline of distributed control of robotic networks sits at the intersection of distinct areas such as distributed algorithms, parallel processing, control, and estimation. Our second objective is to provide a self-contained, broad exposition of the notions and tools from these areas that are relevant in cooperative control problems. These concepts include graph-theoretic notions (connectivity, adjacency and Laplacian matrices), distributed algorithms from computer science (leader election, basic tree computations) and from parallel processing (averaging algorithms, convergence rates), and geometric models and optimization (Voronoi partitions, proximity graphs). Our third objective is to put forth a model for robotic networks that helps to rigorously formalize coordination algorithms running on them. We illustrate how computational geometry plays an important role in modeling the interconnection topology of robotic networks. We draw on classical notions from distributed algorithms to provide complexity measures that characterize the execution of coordination algorithms. Such measures allow us to quantify the algorithm performance and implementation costs. Our fourth objective is to present various algorithms for coordination tasks such as connectivity maintenance, rendezvous, and deployment. We put special emphasis on analyzing the correctness of the algorithms and providing measures of their complexity. StructureThe workshop is structured in two parts. The morning session will consist of
The afternoon session will consist of |