Dataset Viewer
Auto-converted to Parquet
Search is not available for this dataset
observation.image
imagewidth (px)
96
96
observation.state
sequence
action
sequence
next.reward
float32
0
1
next.done
bool
2 classes
next.success
bool
2 classes
index
int64
0
24.5k
episode_index
int64
0
280
frame_index
int64
0
271
timestamp
float32
0
27.1
task_index
int64
0
0
[ 301.78936767578125, 161.84915161132812 ]
[ 286, 189 ]
0
false
false
0
0
0
0
0
[ 297.12091064453125, 169.87689208984375 ]
[ 279, 206 ]
0
false
false
1
0
1
0.1
0
[ 289.99481201171875, 183.5980682373047 ]
[ 278, 206 ]
0
false
false
2
0
2
0.2
0
[ 284.4305419921875, 194.24716186523438 ]
[ 270, 230 ]
0
false
false
3
0
3
0.3
0
[ 278.8337707519531, 207.30067443847656 ]
[ 272, 235 ]
0
false
false
4
0
4
0.4
0
[ 275.20587158203125, 219.47824096679688 ]
[ 273, 269 ]
0
false
false
5
0
5
0.5
0
[ 273.79888916015625, 237.19631958007812 ]
[ 273, 294 ]
0
false
false
6
0
6
0.6
0
[ 273.3205871582031, 259.5173034667969 ]
[ 273, 310 ]
0
false
false
7
0
7
0.7
0
[ 273.1379089355469, 280.768798828125 ]
[ 263, 321 ]
0
false
false
8
0
8
0.8
0
[ 270.1051025390625, 298.276123046875 ]
[ 262, 328 ]
0
false
false
9
0
9
0.9
0
[ 266.57354736328125, 311.5332946777344 ]
[ 263, 356 ]
0
false
false
10
0
10
1
0
[ 264.61669921875, 327.9803161621094 ]
[ 263, 378 ]
0
false
false
11
0
11
1.1
0
[ 263.744384765625, 347.7279052734375 ]
[ 269, 403 ]
0
false
false
12
0
12
1.2
0
[ 265.1198425292969, 369.63946533203125 ]
[ 276, 423 ]
0
false
false
13
0
13
1.3
0
[ 268.9265441894531, 391.570068359375 ]
[ 280, 441 ]
0
false
false
14
0
14
1.4
0
[ 273.4152526855469, 412.1205749511719 ]
[ 284, 446 ]
0
false
false
15
0
15
1.5
0
[ 277.7770080566406, 427.6344909667969 ]
[ 298, 449 ]
0
false
false
16
0
16
1.6
0
[ 284.9336853027344, 437.70977783203125 ]
[ 329, 457 ]
0
false
false
17
0
17
1.7
0
[ 300.2198791503906, 445.78143310546875 ]
[ 341, 455 ]
0
false
false
18
0
18
1.8
0
[ 317.19757080078125, 450.6518859863281 ]
[ 325, 426 ]
0
false
false
19
0
19
1.9
0
[ 324.0392150878906, 444.38134765625 ]
[ 326, 421 ]
0
false
false
20
0
20
2
0
[ 325.4630432128906, 434.7007141113281 ]
[ 327, 409 ]
0.00212
false
false
21
0
21
2.1
0
[ 326.13153076171875, 424.5014343261719 ]
[ 331, 398 ]
0.048259
false
false
22
0
22
2.2
0
[ 327.7417297363281, 413.8045349121094 ]
[ 336, 382 ]
0.120559
false
false
23
0
23
2.3
0
[ 330.7275695800781, 401.4516906738281 ]
[ 337, 375 ]
0.162487
false
false
24
0
24
2.4
0
[ 333.50341796875, 390.0882568359375 ]
[ 331, 352 ]
0.220316
false
false
25
0
25
2.5
0
[ 333.4596252441406, 375.8875427246094 ]
[ 329, 339 ]
0.28291
false
false
26
0
26
2.6
0
[ 331.85614013671875, 360.7347106933594 ]
[ 325, 320 ]
0.34169
false
false
27
0
27
2.7
0
[ 329.3313903808594, 344.5874328613281 ]
[ 370, 418 ]
0.347508
false
false
28
0
28
2.8
0
[ 340.5914001464844, 361.75848388671875 ]
[ 388, 397 ]
0.347508
false
false
29
0
29
2.9
0
[ 359.1682434082031, 380.4295349121094 ]
[ 391, 386 ]
0.347508
false
false
30
0
30
3
0
[ 373.859375, 385.96917724609375 ]
[ 407, 362 ]
0.347508
false
false
31
0
31
3.1
0
[ 387.1883239746094, 379.4804992675781 ]
[ 411, 355 ]
0.347508
false
false
32
0
32
3.2
0
[ 397.9170227050781, 369.5540771484375 ]
[ 411, 353 ]
0.362576
false
false
33
0
33
3.3
0
[ 404.42779541015625, 361.9355773925781 ]
[ 410, 353 ]
0.385591
false
false
34
0
34
3.4
0
[ 407.5231628417969, 357.4575500488281 ]
[ 411, 349 ]
0.392237
false
false
35
0
35
3.5
0
[ 409.16571044921875, 353.9682312011719 ]
[ 403, 387 ]
0.390667
false
false
36
0
36
3.6
0
[ 407.72802734375, 362.79412841796875 ]
[ 409, 386 ]
0.390667
false
false
37
0
37
3.7
0
[ 407.4111022949219, 373.3608093261719 ]
[ 417, 382 ]
0.390667
false
false
38
0
38
3.8
0
[ 410.39324951171875, 378.4897155761719 ]
[ 427, 382 ]
0.390667
false
false
39
0
39
3.9
0
[ 416.37628173828125, 380.47821044921875 ]
[ 442, 386 ]
0.390667
false
false
40
0
40
4
0
[ 425.80523681640625, 382.49774169921875 ]
[ 453, 385 ]
0.390667
false
false
41
0
41
4.1
0
[ 436.7033996582031, 383.8534240722656 ]
[ 459, 378 ]
0.390667
false
false
42
0
42
4.2
0
[ 446.3226623535156, 382.39892578125 ]
[ 460, 370 ]
0.390667
false
false
43
0
43
4.3
0
[ 452.84381103515625, 378.0755920410156 ]
[ 463, 364 ]
0.390667
false
false
44
0
44
4.4
0
[ 457.3621826171875, 372.52960205078125 ]
[ 463, 354 ]
0.390667
false
false
45
0
45
4.5
0
[ 460.1565856933594, 365.4836730957031 ]
[ 454, 344 ]
0.390667
false
false
46
0
46
4.6
0
[ 458.9602355957031, 357.06671142578125 ]
[ 445, 345 ]
0.401132
false
false
47
0
47
4.7
0
[ 454.1390380859375, 351.10650634765625 ]
[ 443, 341 ]
0.432247
false
false
48
0
48
4.8
0
[ 449.28668212890625, 346.78265380859375 ]
[ 436, 333 ]
0.53746
false
false
49
0
49
4.9
0
[ 444.1209411621094, 341.5844421386719 ]
[ 440, 324 ]
0.665738
false
false
50
0
50
5
0
[ 441.4226379394531, 334.84906005859375 ]
[ 436, 311 ]
0.801123
false
false
51
0
51
5.1
0
[ 439.3675231933594, 325.83837890625 ]
[ 429, 312 ]
0.933237
false
false
52
0
52
5.2
0
[ 435.69781494140625, 319.0887451171875 ]
[ 460, 404 ]
0.944573
false
false
53
0
53
5.3
0
[ 441.7261962890625, 342.66229248046875 ]
[ 461, 389 ]
0.944573
false
false
54
0
54
5.4
0
[ 450.1540832519531, 365.8822326660156 ]
[ 462, 354 ]
0.944573
false
false
55
0
55
5.5
0
[ 455.7971496582031, 367.4959411621094 ]
[ 462, 327 ]
0.944573
false
false
56
0
56
5.6
0
[ 458.9437561035156, 354.15814208984375 ]
[ 456, 316 ]
0.944573
false
false
57
0
57
5.7
0
[ 458.7594299316406, 338.3497009277344 ]
[ 448, 306 ]
0.944573
false
false
58
0
58
5.8
0
[ 455.2439880371094, 324.5411682128906 ]
[ 443, 305 ]
0.944573
false
false
59
0
59
5.9
0
[ 450.4210510253906, 315.16839599609375 ]
[ 442, 300 ]
0.944573
false
false
60
0
60
6
0
[ 446.56787109375, 308.5186767578125 ]
[ 440, 295 ]
0.944573
false
false
61
0
61
6.1
0
[ 443.6918029785156, 302.8370666503906 ]
[ 431, 301 ]
0.971658
false
false
62
0
62
6.2
0
[ 439.20977783203125, 300.7909851074219 ]
[ 453, 276 ]
0.977715
false
false
63
0
63
6.3
0
[ 441.87060546875, 293.2651062011719 ]
[ 455, 267 ]
0.977715
false
false
64
0
64
6.4
0
[ 447.30621337890625, 282.7242126464844 ]
[ 471, 300 ]
0.977715
false
false
65
0
65
6.5
0
[ 455.77197265625, 284.9089660644531 ]
[ 464, 308 ]
0.977715
false
false
66
0
66
6.6
0
[ 460.8486633300781, 293.690185546875 ]
[ 458, 317 ]
0.977715
false
false
67
0
67
6.7
0
[ 460.9105224609375, 303.1553955078125 ]
[ 462, 345 ]
0.977715
false
false
68
0
68
6.8
0
[ 460.90771484375, 318.1212463378906 ]
[ 462, 355 ]
0.977715
false
false
69
0
69
6.9
0
[ 461.35479736328125, 333.69439697265625 ]
[ 458, 351 ]
0.977715
false
false
70
0
70
7
0
[ 460.4844055175781, 342.9106140136719 ]
[ 450, 345 ]
0.977715
false
false
71
0
71
7.1
0
[ 457.0079650878906, 345.4395446777344 ]
[ 446, 334 ]
0.977715
false
false
72
0
72
7.2
0
[ 452.58154296875, 342.2786865234375 ]
[ 435, 329 ]
0.977715
false
false
73
0
73
7.3
0
[ 446.1580810546875, 337.0699768066406 ]
[ 433, 327 ]
0.977715
false
false
74
0
74
7.4
0
[ 440.30670166015625, 332.6139221191406 ]
[ 423, 322 ]
0.977715
false
false
75
0
75
7.5
0
[ 433.7288818359375, 328.3576354980469 ]
[ 422, 322 ]
0.988187
false
false
76
0
76
7.6
0
[ 428.3323974609375, 325.2965393066406 ]
[ 459, 365 ]
0.998065
false
false
77
0
77
7.7
0
[ 436.09906005859375, 336.33148193359375 ]
[ 460, 365 ]
0.998065
false
false
78
0
78
7.8
0
[ 446.6088562011719, 349.2589416503906 ]
[ 431, 345 ]
0.998065
false
false
79
0
79
7.9
0
[ 444.6478576660156, 351.18109130859375 ]
[ 423, 341 ]
0.998065
false
false
80
0
80
8
0
[ 436.4817810058594, 347.67303466796875 ]
[ 420, 340 ]
0.998065
false
false
81
0
81
8.1
0
[ 429.1958312988281, 344.2674255371094 ]
[ 413, 337 ]
0.998065
false
false
82
0
82
8.2
0
[ 422.57720947265625, 341.2668151855469 ]
[ 410, 333 ]
1
true
true
83
0
83
8.3
0
[ 367.13824462890625, 168.54605102539062 ]
[ 343, 232 ]
0.376254
false
false
84
1
0
0
0
[ 360.0012512207031, 187.30760192871094 ]
[ 354, 250 ]
0.376254
false
false
85
1
1
0.1
0
[ 355.52362060546875, 212.9501190185547 ]
[ 358, 259 ]
0.376254
false
false
86
1
2
0.2
0
[ 355.6014709472656, 233.5400848388672 ]
[ 364, 289 ]
0.376254
false
false
87
1
3
0.3
0
[ 358.36627197265625, 255.04940795898438 ]
[ 360, 305 ]
0.376254
false
false
88
1
4
0.4
0
[ 359.78802490234375, 275.9958190917969 ]
[ 355, 329 ]
0.376254
false
false
89
1
5
0.5
0
[ 358.5491638183594, 297.2210998535156 ]
[ 343, 370 ]
0.376254
false
false
90
1
6
0.6
0
[ 353.4143371582031, 324.6392822265625 ]
[ 341, 377 ]
0.376254
false
false
91
1
7
0.7
0
[ 348.0059509277344, 348.232666015625 ]
[ 329, 397 ]
0.376254
false
false
92
1
8
0.8
0
[ 341.0075378417969, 368.46246337890625 ]
[ 310, 409 ]
0.376254
false
false
93
1
9
0.9
0
[ 329.7200622558594, 385.8716125488281 ]
[ 290, 422 ]
0.376254
false
false
94
1
10
1
0
[ 314.517333984375, 401.0579833984375 ]
[ 287, 422 ]
0.376254
false
false
95
1
11
1.1
0
[ 301.9556884765625, 411.26641845703125 ]
[ 250, 426 ]
0.376254
false
false
96
1
12
1.2
0
[ 283.54119873046875, 417.9416809082031 ]
[ 230, 428 ]
0.376254
false
false
97
1
13
1.3
0
[ 261.912109375, 422.5504455566406 ]
[ 218, 435 ]
0.376254
false
false
98
1
14
1.4
0
[ 242.97048950195312, 427.3471374511719 ]
[ 216, 437 ]
0.376254
false
false
99
1
15
1.5
0
End of preview. Expand in Data Studio

PushT Dataset

This dataset contains demonstrations for the PushT environment, a robotic manipulation task where an agent needs to push a T-shaped object onto a matching target surface. Each episode is initialized with a randomized T-block and target position and orientation to ensure a more realistic scenario.

Environment Details

The dataset was collected using the gym-pusht environment, which provides a simple 2D robotic pushing task.

  • Task: Push the T-shaped gray block onto the T-shaped green target surface using the blue pointer.
  • Observation Space: RGB images (96×96×3) and agent position (2D coordinates)
  • Action Space: 2D coordinates for the agent position
  • Success Condition: The T-shaped block overlaps sufficiently with the target surface
  • Randomized Goals: This dataset uses a variation of the environment with randomize_goal=True, which randomizes the goal position for each episode, creating a more diverse and challenging dataset.

Dataset Creation

This dataset was created through human demonstrations where a single human operator provided demonstrations of successful task completion.

Dataset Composition

  • States: RGB images and agent position coordinates
  • Actions: 2D position commands for the agent
  • Rewards: Sparse rewards based on task completion
    • Metadata: Success flags and episode information

Usage

This dataset is intended for training imitation learning and reinforcement learning policies for object manipulation tasks.

Loading the Dataset

This dataset was created using LeRobot.

Dataset Structure

meta/info.json:

{
    "codebase_version": "v2.1",
    "robot_type": "2d pointer",
    "total_episodes": 101,
    "total_frames": 9438,
    "total_tasks": 1,
    "total_videos": 0,
    "total_chunks": 1,
    "chunks_size": 1000,
    "fps": 10,
    "splits": {
        "train": "0:281"
    },
    "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
    "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4",
    "features": {
        "observation.image": {
            "dtype": "image",
            "shape": [
                96,
                96,
                3
            ],
            "names": [
                "height",
                "width",
                "channel"
            ]
        },
        "observation.state": {
            "dtype": "float32",
            "shape": [
                2
            ],
            "names": {
                "motors": [
                    "motor_0",
                    "motor_1"
                ]
            }
        },
        "action": {
            "dtype": "float32",
            "shape": [
                2
            ],
            "names": {
                "motors": [
                    "motor_0",
                    "motor_1"
                ]
            }
        },
        "next.reward": {
            "dtype": "float32",
            "shape": [
                1
            ],
            "names": null
        },
        "next.done": {
            "dtype": "bool",
            "shape": [
                1
            ],
            "names": null
        },
        "next.success": {
            "dtype": "bool",
            "shape": [
                1
            ],
            "names": null
        },
        "index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "episode_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "frame_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        },
        "timestamp": {
            "dtype": "float32",
            "shape": [
                1
            ],
            "names": null
        },
        "task_index": {
            "dtype": "int64",
            "shape": [
                1
            ],
            "names": null
        }
    }
}

Citation

BibTeX:

[More Information Needed]
Downloads last month
146