Abstract-This article reviews some main results and progress in distributed multi-agent coordination, with the focus on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs) and unmanned underwater vehicles (UUVs), has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, distributed task assignment, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important therefore deserving further investigations.

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.

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Impairment of working memory is one of the most important deleterious effects of marijuana intoxication in humans, but its underlying mechanisms are presently unknown. Here, we demonstrate that the impairment of spatial working memory (SWM) and in vivo long-term depression (LTD) of synaptic strength at hippocampal CA3-CA1 synapses, induced by an acute exposure of exogenous cannabinoids, is fully abolished in conditional mutant mice lacking type-1 cannabinoid receptors (CB(1)R) in brain astroglial cells but is conserved in mice lacking CB(1)R in glutamatergic or GABAergic neurons. Blockade of neuronal glutamate N-methyl-D-aspartate receptors (NMDAR) and of synaptic trafficking of glutamate α-amino-3-hydroxy-5-methyl-isoxazole propionic acid receptors (AMPAR) also abolishes cannabinoid effects on SWM and LTD induction and expression. We conclude that the impairment of working memory by marijuana and cannabinoids is due to the activation of astroglial CB(1)R and is associated with astroglia-dependent hippocampal LTD in vivo.

This paper considers the distributed consensus problems for multi-agent systems with general linear and Lipschitz nonlinear dynamics. Distributed relative-state consensus protocols with an adaptive law for adjusting the coupling weights between neighboring agents are designed for both the linear and nonlinear cases, under which consensus is reached for all undirected connected communication graphs.Extensions to the case with a leader-follower communication graph are further studied. In contrast to the existing results in the literature, the adaptive consensus protocols here can be implemented by each agent in a fully distributed fashion without using any global information.