  For a multi-robot system equipped with heterogeneous capabilities, this paper
presents a mechanism to allocate robots to tasks in a resilient manner when
anomalous environmental conditions such as weather events or adversarial
attacks affect the performance of robots within the tasks. Our primary
objective is to ensure that each task is assigned the requisite level of
resources, measured as the aggregated capabilities of the robots allocated to
the task. By keeping track of task performance deviations under external
perturbations, our framework quantifies the extent to which robot capabilities
(e.g., visual sensing or aerial mobility) are affected by environmental
conditions. This enables an optimization-based framework to flexibly reallocate
robots to tasks based on the most degraded capabilities within each task. In
the face of resource limitations and adverse environmental conditions, our
algorithm minimally relaxes the resource constraints corresponding to some
tasks, thus exhibiting a graceful degradation of performance. Simulated
experiments in a multi-robot coverage and target tracking scenario demonstrate
the efficacy of the proposed approach.
