SafeManip is a new benchmark that applies LTLf monitors to assess temporal safety properties across eight categories in robotic manipulation, demonstrating that task success frequently fails to ensure safe execution in vision-language-action policies.
If the mechanism hits an obstacle or becomes blocked, retract first and return the fixture to a safe known state rather than continuing to push
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SafeManip: A Property-Driven Benchmark for Temporal Safety Evaluation in Robotic Manipulation
SafeManip is a new benchmark that applies LTLf monitors to assess temporal safety properties across eight categories in robotic manipulation, demonstrating that task success frequently fails to ensure safe execution in vision-language-action policies.