CN-CBF: Composite Neural Control Barrier Function for Safe Robot Navigation in Dynamic Environments

ArXi:2603.06921v1 Announce Type: cross Safe navigation of autonomous robots remains one of the core challenges in the field, especially in dynamic and uncertain environments. One of the prevalent approaches is safety filtering based on control barrier functions (CBFs), which are easy to deploy but difficult to design. Motivated by the shortcomings of existing learning- and model-based methods, we propose a simple yet effective neural CBF design method for safe robot navigation in dynamic environments.