Distributed multi‐vehicle coordinated control via local information exchange

Abstract

SUMMARYThis paper describes a distributed coordination scheme with local information exchange for multiple vehicle systems. We introduce second-order consensus protocols that take into account motions of the information states and their derivatives, extending first-order protocols from the literature. We also derive necessary and sufficient conditions under which consensus can be reached in the context of unidirectional information exchange topologies. This work takes into account the general case where information flow may be unidirectional due to sensors with limited fields of view or vehicles with directed, power-constrained communication links. Unlike the first-order case, we show that having a (directed) spanning tree is a necessary rather than a sufficient condition for consensus seeking with second-order dynamics. This work focuses on a formal analysis of information exchange topologies that permit second-order consensus. Given its importance to the stability of the coordinated system, an analysis of the consensus term control gains is also presented, specifically the strength of the information states relative to their derivatives. As an illustrative example, consensus protocols are applied to coordinate the movements of multiple mobile robots.

Swarming on Random Graphs

“…that Np ≥ q 2 0 log 3/2 N where q 0 > 0 denotes an arbitrary, fixed constant. We then have that there exists an Nindependent constant C so that the estimate (27) holds for all p 0 , q 0 > 0 and N sufficiently large. Substituting the previous estimates (26), (27) into the bound for R 2 , we find…”

“…As shown in Ren [27,29,30], Olfati-Saber [24,25], Moreau [22,23], and Cao [5], the role of connectivity and stability are highly relevant for cooperative control algorithms. For directed graphs with a fixed topology (i.e.…”

Convergence Analysis of Stochastic Consensus over Noisy Networks of Linear Symmetric Agents

“…The states represent conditions of the machines, environment, or agents themselves. For example, they correspond to the positions in vehicle formation problems [2], local time in clock synchronization problems [3], or agent's opinions [4]. Since it is often used over noisy networks in practical situations, its convergence analysis and stopping rule should be established in stochastic settings [5].…”

Consensus Problem of Second-order Dynamic Agents with Heterogeneous Input and Communication Delays

“…For the first-order multi-agent systems with agents' dynamics modeled by single integrators and second-order multi-agent systems with agents' dynamics modeled by double integrators, consensus algorithms have been proposed to solve the consensus problem, and sufficient conditions have been obtained for the system converging to the consensus with static or switched interconnection topology [1][2][3][4].…”