The report
A generated robot plan is not safe merely because its steps are syntactically valid and align with a user's stated task. A language model may misunderstand a person's location, grasp force or the consequences of moving an object. LEASH inserts safety review and action gates between a language-model planner and the robot's ability to act, testing whether dangerous steps are intercepted before they become physical effects. The LEASH paper studies these interventions on a defined set of risky robotics scenarios.
Physical actions are the evaluation unit
The researchers used simulated and physical tasks to compare planning choices and what the robot actually performed. Simulation provides repeatable conditions and controlled hazards, while a small real-hardware sample tests different failure modes. A blocked suggestion is not the same event as a prevented collision or a prevented injury, and a model's judgment about a plan cannot replace an instrumented execution log. The LEASH Case separates the review, gate and motion effects instead of treating their aggregate safety result as universal.
The method also has a permission-design implication. A planning agent should be able to propose useful behavior, but its emitted instructions should not constitute a direct grant to motors and actuators. Independent action gating can constrain execution when a generated plan conflicts with established physical limits, provided those limits accurately represent the hardware and environment. That last proviso matters: outdated state, blind spots and fast-moving hazards can defeat a policy that looked correct at planning time.
A production validation would need per-action overrides, missed hazards, false denials of legitimate work, intervention latency and recovery behavior in unexpected scenes. No deployment-wide injury or availability result follows from the paper's selected tests.