{"ID":2830922,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.10118","arxiv_id":"2512.10118","title":"Explicit Control Barrier Function-based Safety Filters and their Resource-Aware Computation","abstract":"This paper studies the efficient implementation of safety filters that are designed using control barrier functions (CBFs), which minimally modify a nominal controller to render it safe with respect to a prescribed set of states. Although CBF-based safety filters are often implemented by solving a quadratic program (QP) in real time, the use of off-the-shelf solvers for such optimization problems poses a challenge in applications where control actions need to be computed efficiently at very high frequencies. In this paper, we introduce a closed-form expression for controllers obtained through CBF-based safety filters. This expression is obtained by partitioning the state-space into different regions, with a different closed-form solution in each region. We leverage this formula to introduce a resource-aware implementation of CBF-based safety filters that detects changes in the partition region and uses the closed-form expression between changes. We showcase the applicability of our approach in examples ranging from aerospace control to safe reinforcement learning.","short_abstract":"This paper studies the efficient implementation of safety filters that are designed using control barrier functions (CBFs), which minimally modify a nominal controller to render it safe with respect to a prescribed set of states. Although CBF-based safety filters are often implemented by solving a quadratic program (QP...","url_abs":"https://arxiv.org/abs/2512.10118","url_pdf":"https://arxiv.org/pdf/2512.10118v2","authors":"[\"Pol Mestres\",\"Shima Sadat Mousavi\",\"Pio Ong\",\"Lizhi Yang\",\"Ersin Das\",\"Joel W. Burdick\",\"Aaron D. Ames\"]","published":"2025-12-10T22:09:53Z","proceeding":"eess.SY","tasks":"[\"eess.SY\",\"math.OC\"]","methods":"[\"Reinforcement Learning\"]","has_code":false}