Coordinated Control of Multi-Robot Systems: A Survey

Abstract

: Recently, significant gains have been made in our understanding of multi-robot systems, and such systems have been deployed in domains as diverse as precision agriculture, flexible manufacturing, environmental monitoring, search-and-rescue operations, and even swarming robotic toys. What has enabled these developments is a combination of technological advances in performance, price, and scale of the platforms themselves, and a new understanding of how the robots should be organized algorithmically. In this paper, we focus on the latter of these advances, with particular emphasis on decentralized control and coordination strategies as they pertain to multi-robot systems. The paper discusses a class of problems related to the assembly of preferable geometric shapes in a decentralized manner through the formulation of descent-based algorithms defined with respect to team-level performance costs.

An Optimal Task Allocation Strategy for Heterogeneous Multi-Robot Systems

“…Robot i is in charge of surveiling only its Voronoi cell V i . As shown in [9], the cost to minimize in order to execute this surveillance task is given by…”

“…they can be broken down into the sum of pairwise costs among each robot i and its neighboring robots j ∈ N i . In [9], the authors illustrate the various multi-robot tasks represented by such a cost, and demonstrate the decentralized nature of the control law obtained by performing a gradientdescent on this cost. Furthermore, in [13], we showed that in this case, the constraint-based task execution can be rendered decentralized provided that certain conditions on the extended class K function gamma that appears in (14b) are satisfied.…”

“…The execution of the task is identified with the minimization of the cost, whose value is inversely proportional to the extent to which the task has been accomplished. Such a description of multi-robot tasks has been used to generate a wide variety of behaviors, such as environment surveillance and exploration, formationconstrained control and path following [9].…”

Constraint-Driven Coordinated Control of Multi-Robot Systems

“…Local, scalable, safe and emergent are four essential features that decentralized multi-robot coordinated control algorithms should possess [24]. Many algorithms that satisfy these properties have been developed for applications ranging from social behavior mimicking [25], formation assembling [26] and area patrolling [27].…”

Clone Swarms: Learning to Predict and Control Multi-Robot Systems by Imitation

“…Research on modeling, prediction and control of multiagent systems, e.g., teams of quadcopters, autonomous cars, or other forms of unmanned vehicles, has gained considerable attention in a variety of research disciplines. For an excellent recent survey of how such teams can be formalized, coordinated, and controlled, we refer the reader to [7]. Among the formalisms most widely used for representing and studying MRS and swarms are graphtheoretic [8] approaches and methods based on cost functions and auctioning processes [2].…”