paulpacaudapache-2.0
Guardian: RLBench-Fail
Annotated robotic manipulation failure dataset generated in RLBench simulator for training Vision-Language Models on failure detection tasks, with planning and execution failures categorized with fine-grained annotations and reasoning traces.
Downloads82
EpisodesRLBench-Fail execution: 12,358 train / 1,000 val / 1,000 test; planning: 5,808 train / 500 val / 500 test
Why This Matters for Physical AI
This dataset enables training Vision-Language Models to detect and categorize robotic planning and execution failures, which is crucial for building safe and reliable robotic systems that can identify when tasks are failing and require intervention or replanning.
Technical Profile
- Modalities
- rgblanguage
- Robot Embodiments
- robotic_arm_with_gripper
- Environment
- simulation
- Task Types
- manipulationgraspingpick_and_placevisual-question-answering
- Episodes
- RLBench-Fail execution: 12,358 train / 1,000 val / 1,000 test; planning: 5,808 train / 500 val / 500 test
- Data Format
- JSONL
- Annotation Types
- language_instructionsfailure_labelsfailure_categoriesreasoning_tracesaction_labels
- License
- apache-2.0
Access
Need custom rgb data?
Claru builds purpose-built datasets for simulation applications with dense human annotations and quality assurance.
Request a Sample Pack