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Datasets:
H-EmbodVis
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DOMINO

Tasks:
Robotics
Languages:
English
Size:
100K<n<1M
ArXiv:
Tags:
robotics
embodied-ai
dynamic-manipulation
vision-language-action
manipulation
trajectory
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  1. dataset/move_can_pot/ARX-X5_clean_level2_50.zip +3 -0
  2. dataset/move_can_pot/ARX-X5_randomized_level1_200.zip +3 -0
  3. dataset/move_can_pot/aloha-agilex_clean_level1_50.zip +3 -0
  4. dataset/move_can_pot/aloha-agilex_clean_level2_50.zip +3 -0
  5. dataset/move_can_pot/franka-panda_clean_level1_50.zip +3 -0
  6. dataset/move_can_pot/franka-panda_clean_level2_50.zip +3 -0
  7. dataset/move_can_pot/franka-panda_randomized_level1_200.zip +3 -0
  8. dataset/move_can_pot/piper_clean_level1_50.zip +3 -0
  9. dataset/move_can_pot/piper_clean_level2_50.zip +3 -0
  10. dataset/move_can_pot/piper_randomized_level1_200.zip +3 -0
  11. dataset/move_can_pot/ur5-wsg_clean_level1_50.zip +3 -0
  12. dataset/move_can_pot/ur5-wsg_clean_level3_50.zip +3 -0
  13. dataset/move_can_pot/ur5-wsg_randomized_level3_200.zip +3 -0
  14. dataset/place_container_plate/ARX-X5_randomized_level2_200.zip +3 -0
  15. dataset/place_container_plate/ARX-X5_randomized_level3_200.zip +3 -0
  16. dataset/place_container_plate/aloha-agilex_randomized_level2_200.zip +3 -0
  17. dataset/place_container_plate/aloha-agilex_randomized_level3_200.zip +3 -0
  18. dataset/place_container_plate/franka-panda_randomized_level2_200.zip +3 -0
  19. dataset/place_container_plate/franka-panda_randomized_level3_200.zip +3 -0
  20. dataset/place_container_plate/piper_clean_level3_50.zip +3 -0
  21. dataset/place_container_plate/piper_randomized_level3_200.zip +3 -0
  22. dataset/place_container_plate/ur5-wsg_clean_level2_50.zip +3 -0
  23. dataset/place_container_plate/ur5-wsg_randomized_level1_200.zip +3 -0
  24. dataset/place_empty_cup/ARX-X5_clean_level1_50.zip +3 -0
  25. dataset/place_empty_cup/ARX-X5_clean_level2_50.zip +3 -0
  26. dataset/place_empty_cup/ARX-X5_clean_level3_50.zip +3 -0
  27. dataset/place_empty_cup/ARX-X5_randomized_level1_200.zip +3 -0
  28. dataset/place_empty_cup/ARX-X5_randomized_level2_200.zip +3 -0
  29. dataset/place_empty_cup/ARX-X5_randomized_level3_200.zip +3 -0
  30. dataset/place_empty_cup/aloha-agilex_clean_level1_50.zip +3 -0
  31. dataset/place_empty_cup/aloha-agilex_clean_level2_50.zip +3 -0
  32. dataset/place_empty_cup/aloha-agilex_clean_level3_50.zip +3 -0
  33. dataset/place_empty_cup/aloha-agilex_randomized_level1_200.zip +3 -0
  34. dataset/place_empty_cup/aloha-agilex_randomized_level2_200.zip +3 -0
  35. dataset/place_empty_cup/aloha-agilex_randomized_level3_200.zip +3 -0
  36. dataset/place_empty_cup/franka-panda_clean_level1_50.zip +3 -0
  37. dataset/place_empty_cup/franka-panda_clean_level2_50.zip +3 -0
  38. dataset/place_empty_cup/franka-panda_clean_level3_50.zip +3 -0
  39. dataset/place_empty_cup/franka-panda_randomized_level1_200.zip +3 -0
  40. dataset/place_empty_cup/franka-panda_randomized_level2_200.zip +3 -0
  41. dataset/place_empty_cup/franka-panda_randomized_level3_200.zip +3 -0
  42. dataset/place_empty_cup/piper_clean_level1_50.zip +3 -0
  43. dataset/place_empty_cup/piper_clean_level2_50.zip +3 -0
  44. dataset/place_empty_cup/piper_clean_level3_50.zip +3 -0
  45. dataset/place_empty_cup/piper_randomized_level1_200.zip +3 -0
  46. dataset/place_empty_cup/piper_randomized_level2_200.zip +3 -0
  47. dataset/place_empty_cup/piper_randomized_level3_200.zip +3 -0
  48. dataset/place_empty_cup/ur5-wsg_clean_level1_50.zip +3 -0
  49. dataset/place_empty_cup/ur5-wsg_clean_level2_50.zip +3 -0
  50. dataset/place_empty_cup/ur5-wsg_clean_level3_50.zip +3 -0
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