Abstract
Effective exchange of information in multi-robot systems is one of the grand challenges of today’s robotics. Here, we address the problem of simultaneously maximizing the (i) resilience to faults and (ii) area coverage of dynamic multi-robot topologies. We want to avoid the onset of single points of failure, i.e., situations in which the failure of a single robot causes the loss of connectivity in the overall network. Our methodology is based on (i) a three-fold control law and (ii) a distributed online optimization strategy that computes the optimal choice of control parameters for each robot. By doing so, connectivity is not only preserved, but also made resilient to failures as the network topology evolves. To assess the effectiveness of our approach, we ran experiments with a team of eight two-wheeled robots and we evaluated it against the injection of two separate classes of faults: communication and hardware failures. Results show that the proposed approach continues to perform as intended, even in the presence of these hazards.
Highlights
In this paper, we consider the problem of achieving resilience in a system composed by multiple robots using a wireless network to exchange data and coordinate towards a common goal
We experimentally evaluate the methodology proposed in [12]— an online optimization strategy that allows the multi-robot system to compute an optimal set of parameters during its mission, based on the current knowl60 edge of the topology of the network
The rest of this paper is organized as follows: Section 2 contextualizes our work among several other related contributions from recent years; we present background theory regarding network properties in Section 3; we discuss the 75 multi-robot system model under evaluation in Section 4; and Section 5 outlines the proposed control architecture
Summary
We consider the problem of achieving resilience in a system composed by multiple robots using a wireless network to exchange data and coordinate towards a common goal. Pathological situations often exist in which, based on the current topological configuration of the network, failure of a single node leads to the disconnection of the network, and the creation of two (or more) 40 isolated sub-networks The presence of such critical nodes completely defeats the inherent redundancy of homogeneous multi-robot systems. The authors propose a solution to mitigate 45 such fragile configurations: adjusting the topology exploiting a robust control law that blends with other control objectives assigned to the multi-robot system This method was implemented on a real multi-robot system in [11], where the performance is evaluated considering an area coverage task, in the presence robotic failures and imperfect communication.
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