Distributed Coordination Control of Multiagent Systems While Preserving Connectedness

By Meng Ji, Magnus Egerstedt. 2007

890 citations recorded by the source corpus.

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

1. Wei Ren
2. Guanrong Chen
3. Zhongkui Li
4. Yongcan Cao
5. Z. Duan
6. Wenwu Yu
7. Francesco Bullo
8. Jorge Cortés

Citations in the corpus

• Deep Reinforcement Learning for Swarm Systems (2018, background): “Ji and Egerstedt [2007] derive a control mechanism preserving the connectedness of a group of agents with limited communication abilities for the rendezvous and formation control problem.”
• Decentralized event-triggered consensus with general linear dynamics (2014, background): “The authors of Ma and Zhang (2010) established conditions underwhich protocolswill exist that achieve consensus.”
• Sufficient conditions for connectivity maintenance and rendezvous in leader-follower networks (2010, background): “These include Ji and Egerstedt (2007), Schuresko and Cortes (2007), DeGennaro and Jadbabaie (2006), Notarstefano et al. (2006), while direct control laws are also used in Zavlanos and Pappas (2008) in an heterogeneous network.”
• Hybrid Control for Connectivity Preserving Flocking (2009, background): “Distributed maintenance of nearest neighbor links by means of unbounded “edge tension” functions is addressed in [9], where a control hysteresis is also introduced to avoid infinite control inputs when new links are about to be inserted to the network.”
• Distributed Control of Robotic Networks (2009, background): “Ji and Egerstedt (2007 ) design Laplacian-based control laws to solve formation control problems while preserving connectivity .”
• Heterophilious Dynamics Enhances Consensus (2013, methodology): “Classified by the tools of the trade, we mention statistical mechanics [10, 23, 101], clustering and spectral theory of graphs [15, 31, 32, 70, 90], optimization and control [39, 43, 44, 71, 72, 91, 112], game theory [5, 65], jump processes, nonlinear Markov chains, and stochastic analysis [15, 52, ”
• A connectivity-preserving flocking algorithm for multi-agent systems based only on position measurements (2009, background): “This hysteresis is crucial in preserving connectivity of a dynamically interactive network (Ji and Egerstedt 2007; Zavlanos et al. 2007; Su and Wang 2008).”
• Nonsmooth Barrier Functions With Applications to Multi-Robot Systems (2017, background): “For example, collision avoidance represents a typical requirement, and in some multi-agent systems, connectivity among the agents remains important [4].”
• Flocking of multi‐agent dynamical systems with intermittent nonlinear velocity measurements (2012, methodology): “By employing an unbounded artificial potential function with an adding links mechanism [26, 41, 44, 45], the flocking algorithms (7) and (24) not only can steer the multi-agent system to a stable motion but also can preserve the connectivity of the underlying communication network during the…”
• Robust Control of Mobility and Communications in Autonomous Robot Teams (2013, background): “Substantial contributions have been made on algorithms that either constrain or modify trajectories to preserve links, or recover from disconnected topologies [3]–[8].”
• Event-triggered control for multi-agent systems (2009, background): “Several results concerning multi-agent cooperative control have appeared in recent literature involving agreement or consensus algori thms [17], [11],[20], formation control [5], [4], [7], [2] and di stributed estimation [18],[23].”
• Distributed Event-Triggered Control for Multi-Agent Systems (2012, background): “Several results concerning multi-agent cooperative control have appeared in the recent literature involving agreement or consensus algorithms [20], [12],[23], formation control [5], [4], [8], [2] and distributed estimation [21],[25].”
• A Class of Bounded Distributed Control Strategies for Connectivity Preservation in Multi-Agent Systems (2010, background): “In [17]–[19], appropriate nonlinear weights are designed for the edges of the interaction graph to ensure network connectivity.”