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@@ -10,21 +10,36 @@ contributors: Dr. Chris Clark (PI), Greta Perez-Haiek (Lead), Luca Macesanu, Kev
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  environment: rectangular swimming pool at NYU CREO, filled with chlorinated water at about a little over a foot's depth of water. \
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  factors: neutral background (shades of blue hexagons with white rimming), neutral lighting (well-lit and constant), disturbances & distractors (variable)
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- current tasks and episode count: [LAST UPDATED: 8/10/2026]
 
 
 
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- (CONTROL)\
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- "grab red rod" - 101 episodes - 23,550 frames\
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- "grab green rod" - 101 episodes - 26,774 frames\
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- "grab yellow rod" - 101 episodes - 22,628\
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- "grab white rod" - 102 episodes - 26,853 frames (note: 2 episodes were noted as failures)
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- (VARIABLE CURRENTS: a volunteer agitates the water up and down using a mop behind and towards the left of the robot. This generates waves in the pool water.)\
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- "grab green rod under currents" - 25 episodes - 6,547 frames\
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- "grab red rod under currents" - 28 episodes - 9,206 frames\
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- "grab white rod under currents" - 25 episodes - 6,778 frames\
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- "grab yellow rod under currents" - 25 episodes - 6,345 frames
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- note: "non-imu_data" folder regards data collected before upgrade from 6-dim obs. space to a 30-dim obs. space... \
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- that folder is there as a reference, but should not be used to train any new models that expect a 30-dim obs. space.
 
 
 
 
 
 
 
 
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- questions? reach out to greta: gp2583@nyu.edu
 
 
 
 
 
 
 
 
 
 
 
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  environment: rectangular swimming pool at NYU CREO, filled with chlorinated water at about a little over a foot's depth of water. \
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  factors: neutral background (shades of blue hexagons with white rimming), neutral lighting (well-lit and constant), disturbances & distractors (variable)
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+ This folder contains 8 LeRobot-format (codebase_version v3.0) datasets recorded\
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+ on a BlueROV2 performing rod-grabbing tasks in a pool, with and without\
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+ simulated currents. Each dataset is packaged as a .zip containing the\
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+ standard LeRobot layout (data/, meta/, videos/).\
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+ Counts below are taken from each dataset's meta/info.json.
 
 
 
 
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+ - Episodes = total_episodes (number of recorded episode/trajectory runs)\
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+ - Frames = total_frames (total timesteps across all episodes, fps = 50.0)\
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+ - Trajectories = total_successes (episodes that ended in a successful grab)\
 
 
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+ Dataset Episodes Frames Trajectories (successes)\
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+ ------------------------------------------------------------------------------\
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+ grab green rod 101 26774 101\
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+ grab green rod under currents 110 37982 101\
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+ grab red rod 101 23550 101\
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+ grab red rod under currents 102 30171 101\
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+ grab white rod 102 26853 100\
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+ grab white rod under currents 101 27934 101\
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+ grab yellow rod 101 22628 101\
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+ grab yellow rod under currents 102 28220 101\
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+ Notes:\
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+ - "Episodes" counts every recorded run, including any that did not end in a\
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+ successful grasp; "Trajectories" (total_successes) counts only the\
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+ successful ones. In most of these datasets nearly all episodes succeeded\
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+ (only "grab white rod" has 2 non-successful episodes: 102 episodes vs 100\
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+ successes).\
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+ - Frame count varies with episode length/duration, not just episode count —\
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+ e.g. "grab green rod under currents" has the most episodes (110) and by far\
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+ the most frames (37982), consistent with currents making the task take\
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+ longer per episode.\
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+ - robot_type: bluerov2, single task per dataset (total_tasks = 1).