Resilient Task Allocation in Heterogeneous Multi-Robot Systems

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