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tartandrive

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train · 63.1k rows

image imagewidth (px) 1.02k 1.02k	lang_goal stringlengths 47 49	trajectory_2d sequencelengths 1 491	trajectory_3d sequencelengths 1 491	camera_params stringclasses 1 value	horizon int64 1 491
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	Navigate to <point x="85.0" y="10.5">goal</point>	[ [ 530, 508 ], [ 530, 475 ], [ 531, 448 ], [ 530, 425 ], [ 530, 404 ], [ 530, 387 ], [ 529, 370 ], [ 529, 357 ], [ 529, 344 ], [ 529, 334 ], [ 528, 324 ], [ 529, 316 ], [ ...	[ [ 4.858197494332213, -0.12861377831456622, -0.016108075728772597 ], [ 5.1704041197937975, -0.13123117937263373, -0.023055086458573015 ], [ 5.469719789503266, -0.12562435176459985, -0.024392637430965536 ], [ 5.761882027357004, -0.12154159618180671, -0.02388...	{"resolution": {"width": 1024, "height": 544}, "camera_matrix": {"data": [477.6049499511719, 0.0, 499.5, 0.0, 477.6049499511719, 252.0, 0.0, 0.0, 1.0], "rows": 3, "cols": 3}, "T_imu_to_camera": {"data": [0.96917189, -0.04204002, 0.24277247, 0.38786055, 0.04768227, 0.99871085, -0.01740936, 0.00734094, -0.24172764, 0.02844865, 0.96992705, 0.31545253, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}, "T_imu_to_rear_ground": {"data": [1.0, 0.0, 0.0, -1.85, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, -2.05, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}, "T_camera_to_optical": {"data": [0.0, -1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}}	327
	Navigate to <point x="85.1" y="11.2">goal</point>	[ [ 532, 507 ], [ 532, 475 ], [ 532, 448 ], [ 531, 424 ], [ 531, 405 ], [ 531, 386 ], [ 530, 371 ], [ 530, 357 ], [ 530, 345 ], [ 529, 335 ], [ 529, 326 ], [ 530, 318 ], [ ...	[ [ 4.898379703585718, -0.1499955352684239, -0.043382687891698524 ], [ 5.197689399886443, -0.1444363344104218, -0.04581099558325086 ], [ 5.489852347608473, -0.140412056633906, -0.04637557127834402 ], [ 5.7887456864845035, -0.13728719081277774, -0.04124917721...	{"resolution": {"width": 1024, "height": 544}, "camera_matrix": {"data": [477.6049499511719, 0.0, 499.5, 0.0, 477.6049499511719, 252.0, 0.0, 0.0, 1.0], "rows": 3, "cols": 3}, "T_imu_to_camera": {"data": [0.96917189, -0.04204002, 0.24277247, 0.38786055, 0.04768227, 0.99871085, -0.01740936, 0.00734094, -0.24172764, 0.02844865, 0.96992705, 0.31545253, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}, "T_imu_to_rear_ground": {"data": [1.0, 0.0, 0.0, -1.85, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, -2.05, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}, "T_camera_to_optical": {"data": [0.0, -1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}}	333
	Navigate to <point x="85.2" y="11.0">goal</point>	[ [ 532, 538 ], [ 532, 500 ], [ 531, 469 ], [ 531, 442 ], [ 531, 419 ], [ 530, 399 ], [ 530, 382 ], [ 530, 366 ], [ 529, 353 ], [ 529, 341 ], [ 529, 332 ], [ 529, 322 ], [ ...	[ [ 4.616667612036466, -0.1470422743550941, -0.007768756162378487 ], [ 4.915974359760739, -0.14089113241345785, -0.008623104797425896 ], [ 5.208127822623695, -0.1362953828923139, -0.00765625295503547 ], [ 5.506983826461539, -0.13260592027242524, -0.000966741...	{"resolution": {"width": 1024, "height": 544}, "camera_matrix": {"data": [477.6049499511719, 0.0, 499.5, 0.0, 477.6049499511719, 252.0, 0.0, 0.0, 1.0], "rows": 3, "cols": 3}, "T_imu_to_camera": {"data": [0.96917189, -0.04204002, 0.24277247, 0.38786055, 0.04768227, 0.99871085, -0.01740936, 0.00734094, -0.24172764, 0.02844865, 0.96992705, 0.31545253, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}, "T_imu_to_rear_ground": {"data": [1.0, 0.0, 0.0, -1.85, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, -2.05, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}, "T_camera_to_optical": {"data": [0.0, -1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}}	327
	Navigate to <point x="85.1" y="10.1">goal</point>	[ [ 532, 529 ], [ 531, 493 ], [ 530, 461 ], [ 530, 435 ], [ 529, 412 ], [ 529, 392 ], [ 529, 375 ], [ 528, 361 ], [ 528, 347 ], [ 528, 337 ], [ 528, 327 ], [ 527, 318 ], [ ...	[ [ 4.6441630155489975, -0.12635177988806134, 0.03025152678960108 ], [ 4.9362780499640735, -0.12057607948577953, 0.03359061835822441 ], [ 5.235052509370242, -0.115678230054165, 0.042706878800208514 ], [ 5.540457398988568, -0.11774263625478198, 0.038552465356...	{"resolution": {"width": 1024, "height": 544}, "camera_matrix": {"data": [477.6049499511719, 0.0, 499.5, 0.0, 477.6049499511719, 252.0, 0.0, 0.0, 1.0], "rows": 3, "cols": 3}, "T_imu_to_camera": {"data": [0.96917189, -0.04204002, 0.24277247, 0.38786055, 0.04768227, 0.99871085, -0.01740936, 0.00734094, -0.24172764, 0.02844865, 0.96992705, 0.31545253, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}, "T_imu_to_rear_ground": {"data": [1.0, 0.0, 0.0, -1.85, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, -2.05, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}, "T_camera_to_optical": {"data": [0.0, -1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}}	328
	Navigate to <point x="85.1" y="9.6">goal</point>	[ [ 533, 526 ], [ 532, 489 ], [ 531, 459 ], [ 530, 432 ], [ 530, 410 ], [ 530, 390 ], [ 529, 374 ], [ 528, 360 ], [ 528, 348 ], [ 528, 337 ], [ 528, 327 ], [ 527, 317 ], [ ...	[ [ 4.673900116963612, -0.10678618123081662, 0.021705897502044103 ], [ 4.972676707075461, -0.10173419942370998, 0.030666891191388324 ], [ 5.278080529559279, -0.10374809194639312, 0.026410487076375055 ], [ 5.592179707053255, -0.1052973742679626, 0.03131924971...	{"resolution": {"width": 1024, "height": 544}, "camera_matrix": {"data": [477.6049499511719, 0.0, 499.5, 0.0, 477.6049499511719, 252.0, 0.0, 0.0, 1.0], "rows": 3, "cols": 3}, "T_imu_to_camera": {"data": [0.96917189, -0.04204002, 0.24277247, 0.38786055, 0.04768227, 0.99871085, -0.01740936, 0.00734094, -0.24172764, 0.02844865, 0.96992705, 0.31545253, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}, "T_imu_to_rear_ground": {"data": [1.0, 0.0, 0.0, -1.85, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, -2.05, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}, "T_camera_to_optical": {"data": [0.0, -1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}}	333
	Navigate to <point x="85.1" y="9.2">goal</point>	[ [ 533, 521 ], [ 532, 486 ], [ 531, 455 ], [ 530, 430 ], [ 530, 407 ], [ 529, 389 ], [ 529, 373 ], [ 529, 360 ], [ 529, 348 ], [ 528, 336 ], [ 528, 326 ], [ 528, 315 ], [ ...	[ [ 4.713592488584062, -0.09182131733329157, 0.020886993312906554 ], [ 5.018994047212264, -0.0936628536224049, 0.01639653026675436 ], [ 5.3330979625988775, -0.09498768406285762, 0.021061794657807553 ], [ 5.640809432901431, -0.10360060462545562, 0.01738709264...	{"resolution": {"width": 1024, "height": 544}, "camera_matrix": {"data": [477.6049499511719, 0.0, 499.5, 0.0, 477.6049499511719, 252.0, 0.0, 0.0, 1.0], "rows": 3, "cols": 3}, "T_imu_to_camera": {"data": [0.96917189, -0.04204002, 0.24277247, 0.38786055, 0.04768227, 0.99871085, -0.01740936, 0.00734094, -0.24172764, 0.02844865, 0.96992705, 0.31545253, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}, "T_imu_to_rear_ground": {"data": [1.0, 0.0, 0.0, -1.85, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, -2.05, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}, "T_camera_to_optical": {"data": [0.0, -1.0, 0.0, 0.0, 0.0, 0.0, -1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0], "rows": 4, "cols": 4}}	330
	Navigate to <point x="85.1" y="8.6">goal</point>	[[533,517],[532,480],[531,451],[531,426],[530,405],[529,387],[529,372],[529,358],[528,346],[528,334](...TRUNCATED)	[[4.753642146520992,-0.07814229801282124,0.018437967284006263],[5.067742774809581,-0.078920073979489(...TRUNCATED)	"{\"resolution\": {\"width\": 1024, \"height\": 544}, \"camera_matrix\": {\"data\": [477.60494995117(...TRUNCATED)	329
	Navigate to <point x="85.2" y="8.3">goal</point>	[[532,510],[530,476],[530,446],[529,423],[528,402],[528,385],[528,370],[528,356],[527,343],[527,330](...TRUNCATED)	[[4.786884180861147,-0.07067732226285983,0.03856418360859415],[5.0946246844442875,-0.078637857515154(...TRUNCATED)	"{\"resolution\": {\"width\": 1024, \"height\": 544}, \"camera_matrix\": {\"data\": [477.60494995117(...TRUNCATED)	330

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TartanDrive Navigation Dataset

This dataset contains navigation trajectory data for robotic navigation tasks. Each example includes an RGB image, a language goal describing the desired navigation target, and 2D/3D trajectories showing the path to the goal.

Dataset Structure

image: RGB image from the robot's viewpoint
lang_goal: Natural language instruction describing the navigation goal
trajectory_2d: 2D trajectory coordinates (pixel space)
trajectory_3d: 3D trajectory coordinates (world space)
camera_params: Camera parameters including intrinsics and extrinsics
horizon: Number of steps in the trajectory

Dataset Statistics

Total examples: 79023
Training examples: 63052
Validation examples: 15971
Total size: 14.65 GB
Number of files: 9

Downloads last month: 15

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