RAN-IP: A Resilient Autonomous Navigation In-the-Loop

This project is complementary to resilient distributed algorithms, where there are growing concerns and challenges with the flow and the use of information in communication networks that affect cyber-physical systems (CPS). The state-of-the-art machine learning models in dynamical systems are vulnerable to adversarial attacks, which can jeopardize hardware and software systems when using such models. This project incorporates a testbed to test resilient distributed optimization (RDO) algorithms in real-time autonomous navigation systems to support current and foreseeable research projects.