Robust Safe

Robust safe control focuses on designing controllers that guarantee the safety of dynamic systems despite uncertainties in their models or environments. Current research emphasizes developing algorithms, such as robust adaptive control barrier functions (raCBFs) and convex semi-infinite programming, to synthesize controllers that are both safe and performant, even under multi-modal uncertainties and control limits. This work is particularly relevant for human-robot interaction and other applications requiring high reliability in uncertain conditions, promising improved safety and efficiency in various domains. The development of less conservative and more computationally tractable methods remains a key focus.