Decentralized estimation and control of graph connectivity in mobile sensor networks

By Penghui Yang, Randy A. Freeman, Geoffrey J. Gordon, Kevin M. Lynch, Siddhartha S. Srinivasa, Rahul Sukthankar. 2008

453 citations recorded by the source corpus.

The ability of a robot team to reconfigure itself is useful in many applications: for metamorphic robots to change shape, for swarm motion towards a goal, for biological systems to avoid predators, or for mobile buoys to clean up oil spills. In many situations, auxiliary constraints, such as connectivity between team members and limits on the maximum hop-count, must be satisfied during reconfiguration. In this paper, we show that both the estimation and control of the graph connectivity can be accomplished in a decentralized manner. We describe a decentralized estimation procedure that allows each agent to track the algebraic connectivity of a time-varying graph. Based on this estimator, we further propose a decentralized gradient controller for each agent to maintain global connectivity during motion.

Subfields: Computer Networks and Communications

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

Citations in the corpus

An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination (2012, background): “Main research in this topic has been reported in [ 163], [270]–[275], where the joint estimation and control problem was considered subject to disturbances [ 270], [272], [273] or without disturbances [ 163], [271], [274], [275].”
Event-triggered communication and control of networked systems for multi-agent consensus (2017, methodology): “There are indeed methods for estimating this quantity in a distributed way (see e.g., Aragues, Shi, Dimarogonas, Sagues, and Johansson (2012) and Yang et al. (2010)) but we do not discuss this here.”
Event-based broadcasting for multi-agent average consensus (2013, methodology): “A more advanced method to resolve this issue is through distributed estimation of λ 2 ( G ) , see Yang et al. (2010).”
Graph-theoretic connectivity control of mobile robot networks (2011, background): “Ways to overcome this problem involve either positive definiteness constraints on the determinant of the Laplacian matrix that is a differentiable function of the Laplacian [43], or distributed consensus on either Laplacian eigenvectors [44], [45] or on the network structure itself [46] for local es”
Distributed Seeking of Nash Equilibria With Applications to Mobile Sensor Networks (2012, background): “Thi s is typical in connectivity control problems [25]–[28].”