SOURCE-LINKED INTELLIGENCE
BarrierFormer: Transformer-Guided Predictive Barrier Enforcement for Safe Robot Control
Control barrier functions (CBFs) have become one of the most popular tools for encoding and enforcing state constraints in safety-critical robotics. Standard CBF approaches are inherently myopic in nature as they enforce safety only at the current time step. Consequently, the system can be driven toward the boundary of the safe set where no feasible safe control exists at a future timestep. Model predictive control (MPC) based approaches address this by enforcing state constraints over a receding horizon. However, such approaches generally require the model to be known for solving a constraine
Read original source ↗ Open in workspace
- recordType
- paper
- region
- Global
Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-20T22:03:18.000Z
First collected: 2026-09-23T09:51:33.063Z. This is not the publication date.