collaborators

14 papers

math.OC2026

Safe Stabilizing Linear Feedback: Necessary and Sufficient Conditions, Optimality, and Margins

Pol Mestres, Shima Sadat Mousavi, Pio Ong +1

Control barrier functions (CBFs) have become an important controller design tool for autonomous systems subject to safety constraints. Despite their popularity, recent works have s…

eess.SY2026

Explicit Control Barrier Function-based Safety Filters and their Resource-Aware Computation

Pol Mestres, Shima Sadat Mousavi, Pio Ong +4

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…

eess.SY2026

Safety Filtering with an Infinite Number of Constraints

Max H. Cohen, Pio Ong, Pol Mestres +1

Control barrier functions (CBFs) provide a rigorous framework for designing controllers enforcing safety constraints. While CBF theory is well-developed for a finite number of safe…

eess.SY2026

SafeSpace: Aggregating Safe Sets from Backup Control Barrier Functions under Input Constraints

Pio Ong, David E. J. van Wijk, Massimiliano de Sa +2

Control barrier functions (CBFs) provide a principled framework for enforcing safety in control systems -- yet the certified safe operating region in practice is often conservative…

math.OC2026

High-Order Matrix Control Barrier Functions: Well-Posedness and Feasibility via Matrix Relative Degree

Samuel G. Gessow, Pio Ong, Aaron D. Ames +1

Control barrier functions (CBFs) provide an effective framework for enforcing safety in dynamical systems with scalar constraints. However, many safety constraints are more natural…

eess.SY2026

Steering with Contingencies: Combinatorial Stabilization and Reach-Avoid Filters

Yana Lishkova, Pio Ong, Sander Tonkens +2

In applications such as autonomous landing and navigation, it is often desirable to steer toward a target while retaining the ability to divert to at least (out of ) alterna…