One False Obstacle Claim Could Redirect a Robot Fleet

The study conditions on a successful semantic manipulation in which a false obstacle claim has already entered an LLM-powered multi-robot system. Rather than making one binary trust decision, its verifier sends selected robots to inspect consequential regions, lets a limited subset adapt provisionally and holds the rest to trusted plans. Simulated transport experiments measure path cost, makespan, coverage and cascade containment across impacts and team sizes. The authors report that team-level verification reduced downstream physical consequences, but the evidence is from one modeled environment rather than deployed fleets.