Teaching Safety to Machines: How Inverse Constraint Learning Reimagines Control Barrier Functions
Factory robots, drones, and autonomous vehicles do not usually fail because nobody cared about safety. They fail because “safe” is annoyingly difficult to write down. An operator may know that a drone should not scrape the ground, that a warehouse robot should not cut across a human worker’s path, or that an autonomous car should not tailgate even when the road is technically clear. But turning that judgement into a formal mathematical boundary is another matter. The physical system has dynamics. The controller has limits. The dangerous state may not be a simple wall or circle. And the difference between “safe enough” and “please do not put that in production” may live in patterns of behaviour rather than in a clean rule. ...