Researchers developed a planner that utilizes uncertainty-driven adaptive vision-language model predictions for off-road navigation. This planner, UDAV, can reduce mean average displacement error by 25.1% compared to deterministic planning, while also providing actionable uncertainty signals for mitigating large planning errors.