  We propose a framework for resilience in a networked heterogeneous
multi-robot team subject to resource failures. Each robot in the team is
equipped with resources that it shares with its neighbors. Additionally, each
robot in the team executes a task, whose performance depends on the resources
to which it has access. When a resource on a particular robot becomes
unavailable (\eg a camera ceases to function), the team optimally reconfigures
its communication network so that the robots affected by the failure can
continue their tasks. We focus on a monitoring task, where robots individually
estimate the state of an exogenous process. We encode the end-to-end effect of
a robot's resource loss on the monitoring performance of the team by defining a
new stronger notion of observability -- \textit{one-hop observability}. By
abstracting the impact that {low-level} individual resources have on the task
performance through the notion of one-hop observability, our framework leads to
the principled reconfiguration of information flow in the team to effectively
replace the lost resource on one robot with information from another, as long
as certain conditions are met. Network reconfiguration is converted to the
problem of selecting edges to be modified in the system's communication graph
after a resource failure has occurred. A controller based on finite-time
convergence control barrier functions drives each robot to a spatial location
that enables the communication links of the modified graph. We validate the
effectiveness of our framework by deploying it on a team of differential-drive
robots estimating the position of a group of quadrotors.
