r2b Dataset 2023

Dataset Overview

The r2b dataset 2023 is a collection of sequences stored in rosbags, a ROS 2 native format used for message data including time synchronized sensor captures from a robot. The dataset can be loaded and played back into an application running a ROS graph of nodes for testing and performance benchmarking of image processing, perception and localization. Each sequence consists of a single sequence in a scene, providing a small diversity of data across the collection of sequences in this dataset.

Several sequences contain sensor multi-second captures including LIDAR, stereo camera, and IMU data from HAWK stereo camera, RealSense D455, and XT32 with highly precise time synchronization. Other sequences contain data recorded from a simulated scene in Isaac Sim. The r2b_hope sequence is distinct as it contains D415 RGB data.

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

tr:nth-child(odd)]:bg-surface-sunken\">

Sequence	Visual	Description
`r2b_lounge`	$\"r2b_lounge$	Lounge sequence containing couch, table, chairs, and staircase with natural planted background wall.
`r2b_storage`	$\"r2b_storage$	Storage sequence including person, AprilTag, shoe, shelving, boxes, pallets, with moving obstacles.
`r2b_hallway`	$\"r2b_hallway$	Hallway sequence with walking persons, low to no feature not-perpendicular walls, specular highlights, and reflections.
`r2b_datacenter`	$\"r2b_datacenter$	Datacenter sequence with tall vertical corridor, repetitive low-feature surfaces, and little color.
`r2b_cafe`	$\"r2b_cafe$	Café sequence including table, chairs, stools, reflective flooring, dark reflective glass walls, specular highlights, low wall features, and vibration from floor surface.
`r2b_hope`	$\"r2b_hope$	Images from `scene_0005` of the HOPE dataset for 6-DoF pose estimation
`r2b_hideaway`	$\"r2b_hideaway$	Hideaway sequence including table, chairs, seated and moving persons, specular highlights, low wall features, and vibration from floor surface.
`r2b_mezzanine`	$\"r2b_mezzanine$	Mezzanine sequence including staircase, railings, table, chairs, highlights, low wall features, and vibration from floor surface.

Documentation

Topics Provided

The sequences contained in this dataset contain the following topics:

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

tr:nth-child(odd)]:bg-surface-sunken\">

Sequence	Topics Provided	Message Type
`r2b_lounge` `r2b_storage` `r2b_hallway` `r2b_datacenter` `r2b_cafe` `r2b_hideaway` `r2b_mezzanine`	`d455_1_depth_camera_info` `d455_1_depth_image` `d455_1_imu` `d455_1_left_ir_camera_info` `d455_1_left_ir_image` `d455_1_rgb_camera_info` `d455_1_rgb_image` `d455_1_right_ir_camera_info` `d455_1_right_ir_image` `hawk_0_left_rgb_camera_info` `hawk_0_left_rgb_image` `hawk_0_right_rgb_camera_info` `hawk_0_right_rgb_image` `pandar_xt_32_0_lidar`	`sensor_msgs/msg/CameraInfo` `sensor_msgs/msg/Image` `sensor_msgs/msg/Imu` `sensor_msgs/msg/CameraInfo` `sensor_msgs/msg/Image` `sensor_msgs/msg/CameraInfo` `sensor_msgs/msg/Image` `sensor_msgs/msg/CameraInfo` `sensor_msgs/msg/Image` `sensor_msgs/msg/CameraInfo` `sensor_msgs/msg/Image` `sensor_msgs/msg/CameraInfo` `sensor_msgs/msg/Image` `sensor_msgs/msg/PointCloud2`
`r2b_hope`	`camera_info` `image`	`sensor_msgs/msg/CameraInfo` `sensor_msgs/msg/Image`

MD5 Checksums

A MD5 checksum of each rosbag is provided to verify the dataset sequence used in testing or benchmarking matches, to detect inconsistencies in input data, and to provide a method to confirm that the same input dataset sequence is used when comparing independent results.

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

tr:nth-child(odd)]:bg-surface-sunken\">

Sequence	Checksum	Size
`r2b_lounge`	720ce30055ee3d49e760f384ad402a03	3.9G
`r2b_storage`	5e8f11201fe10dbac7307a8628553e94	2.9G
`r2b_hallway`	7cc6b54751d37a78893d5bea43b3fbf5	1.3G
`r2b_datacenter`	188167fd025d5922940fb9531f835691	1.7G
`r2b_cafe`	8ef0e6b552cb19b7486cc747f3f3fa43	1.2G
`r2b_hope`	22260103ef97ce5cf563e2c6ee656a4e	30M
`r2b_hideaway`	96a3c2b8007173f9da57e848b4fcee8c	1.8G
`r2b_mezzanine`	c84d7420c5524d882f1019d350232fb1	2.0G

Getting Started/Example

Download the dataset to your local system, and playback the rosbag for test or benchmarking.

ros2 bag play path/to/r2b_sequence\n

For more information about using this dataset for benchmarking ROS 2 graphs of nodes, see ros2_benchmark.

License

This dataset is licensed under Creative Commons - Attribution 4.0 International.

Ethical Considerations

This dataset consists of captures in NVIDIA’s facilities in the United States. Persons in the datasets have consented to use of their images.

This dataset is not sufficiently diverse to be representative of the public in general.

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\n\n# r2b Dataset 2023\n\n## Dataset Overview\n\nThe r2b dataset 2023 is a collection of sequences stored in [rosbags](https://github.com/ros2/design/blob/ros2bags/articles/rosbags.md), a ROS 2 native format used for message data including time synchronized sensor captures from a robot. The dataset can be loaded and played back into an application running a ROS graph of nodes for testing and performance benchmarking of image processing, perception and localization. Each sequence consists of a single sequence in a scene, providing a small diversity of data across the collection of sequences in this dataset.\n\nSeveral sequences contain sensor multi-second captures including LIDAR, stereo camera, and IMU data from [HAWK stereo camera](https://www.leopardimaging.com/li-ar0234cs-stereo-gmsl2-hawk/), [RealSense D455](https://www.intelrealsense.com/depth-camera-d455/), and [XT32](https://www.hesaitech.com/product/xt32/) with highly precise time synchronization. Other sequences contain data recorded from a simulated scene in [Isaac Sim](https://developer.nvidia.com/isaac-sim). The `r2b_hope` sequence is distinct as it contains [D415](https://www.intelrealsense.com/depth-camera-d415/) RGB data.\n\n| Sequence | Visual | Description |\n| ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| `r2b_lounge` | ![r2b_lounge sequence](https://media.githubusercontent.com/media/NVIDIA-ISAAC-ROS/ros2_benchmark/main/resources/r2b_lounge_sequence.gif) | Lounge sequence containing couch, table, chairs, and staircase with natural planted background wall. |\n| `r2b_storage` | ![r2b_storage sequence](https://media.githubusercontent.com/media/NVIDIA-ISAAC-ROS/ros2_benchmark/main/resources/r2b_storage_sequence.gif) | Storage sequence including person, AprilTag, shoe, shelving, boxes, pallets, with moving obstacles. |\n| `r2b_hallway` | ![r2b_hallway sequence](https://media.githubusercontent.com/media/NVIDIA-ISAAC-ROS/ros2_benchmark/main/resources/r2b_hallway_sequence.gif) | Hallway sequence with walking persons, low to no feature not-perpendicular walls, specular highlights, and reflections. |\n| `r2b_datacenter` | ![r2b_datacenter sequence](https://media.githubusercontent.com/media/NVIDIA-ISAAC-ROS/ros2_benchmark/main/resources/r2b_datacenter_sequence.gif) | Datacenter sequence with tall vertical corridor, repetitive low-feature surfaces, and little color. |\n| `r2b_cafe` | ![r2b_cafe sequence](https://media.githubusercontent.com/media/NVIDIA-ISAAC-ROS/ros2_benchmark/main/resources/r2b_cafe_sequence.gif) | Café sequence including table, chairs, stools, reflective flooring, dark reflective glass walls, specular highlights, low wall features, and vibration from floor surface. |\n| `r2b_hope` | ![r2b_hope sequence](https://media.githubusercontent.com/media/NVIDIA-ISAAC-ROS/ros2_benchmark/main/resources/r2b_hope_sequence.gif) | Images from `scene_0005` of the HOPE dataset for 6-DoF pose estimation |\n| `r2b_hideaway` | ![r2b_hideaway sequence](https://media.githubusercontent.com/media/NVIDIA-ISAAC-ROS/ros2_benchmark/main/resources/r2b_hideaway_sequence.gif) | Hideaway sequence including table, chairs, seated and moving persons, specular highlights, low wall features, and vibration from floor surface. |\n| `r2b_mezzanine` | ![r2b_mezzanine sequence](https://media.githubusercontent.com/media/NVIDIA-ISAAC-ROS/ros2_benchmark/main/resources/r2b_mezzanine_sequence.gif) | Mezzanine sequence including staircase, railings, table, chairs, highlights, low wall features, and vibration from floor surface. |\n\n## Documentation\n\n### Topics Provided\n\nThe sequences contained in this dataset contain the following topics:\n\n| Sequence | Topics Provided | Message Type |\n| --------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| `r2b_lounge`
`r2b_storage`
`r2b_hallway`
`r2b_datacenter`
`r2b_cafe`
`r2b_hideaway`
`r2b_mezzanine` | `d455_1_depth_camera_info`
`d455_1_depth_image`
`d455_1_imu`
`d455_1_left_ir_camera_info`
`d455_1_left_ir_image`
`d455_1_rgb_camera_info`
`d455_1_rgb_image`
`d455_1_right_ir_camera_info`
`d455_1_right_ir_image`
`hawk_0_left_rgb_camera_info`
`hawk_0_left_rgb_image`
`hawk_0_right_rgb_camera_info`
`hawk_0_right_rgb_image`
`pandar_xt_32_0_lidar` | `sensor_msgs/msg/CameraInfo`
`sensor_msgs/msg/Image`
`sensor_msgs/msg/Imu`
`sensor_msgs/msg/CameraInfo`
`sensor_msgs/msg/Image`
`sensor_msgs/msg/CameraInfo`
`sensor_msgs/msg/Image`
`sensor_msgs/msg/CameraInfo`
`sensor_msgs/msg/Image`
`sensor_msgs/msg/CameraInfo`
`sensor_msgs/msg/Image`
`sensor_msgs/msg/CameraInfo`
`sensor_msgs/msg/Image`
`sensor_msgs/msg/PointCloud2` |\n| `r2b_hope` | `camera_info`
`image` | `sensor_msgs/msg/CameraInfo`
`sensor_msgs/msg/Image` |\n\n### MD5 Checksums\n\nA MD5 checksum of each rosbag is provided to verify the dataset sequence used in testing or benchmarking matches, to detect inconsistencies in input data, and to provide a method to confirm that the same input dataset sequence is used when comparing independent results.\n\n| Sequence | Checksum | Size |\n| ---------------- | -------------------------------- | ---- |\n| `r2b_lounge` | 720ce30055ee3d49e760f384ad402a03 | 3.9G |\n| `r2b_storage` | 5e8f11201fe10dbac7307a8628553e94 | 2.9G |\n| `r2b_hallway` | 7cc6b54751d37a78893d5bea43b3fbf5 | 1.3G |\n| `r2b_datacenter` | 188167fd025d5922940fb9531f835691 | 1.7G |\n| `r2b_cafe` | 8ef0e6b552cb19b7486cc747f3f3fa43 | 1.2G |\n| `r2b_hope` | 22260103ef97ce5cf563e2c6ee656a4e | 30M |\n| `r2b_hideaway` | 96a3c2b8007173f9da57e848b4fcee8c | 1.8G |\n| `r2b_mezzanine` | c84d7420c5524d882f1019d350232fb1 | 2.0G |\n\n## Getting Started/Example\n\nDownload the dataset to your local system, and playback the rosbag for test or benchmarking.\n\n```bash\nros2 bag play path/to/r2b_sequence\n```\n\nFor more information about using this dataset for benchmarking ROS 2 graphs of nodes, see [`ros2_benchmark`](https://github.com/NVIDIA-ISAAC-ROS/ros2_benchmark).\n\n## License\n\nThis dataset is licensed under [Creative Commons - Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/).\n\n## Ethical Considerations\n\nThis dataset consists of captures in NVIDIA’s facilities in the United States. Persons in the datasets have consented to use of their images. \n\nThis dataset is not sufficiently diverse to be representative of the public in general.\n\n

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This tracking cookie allows a website to link visitor behaviour to the recipient of an email marketing campaign, to measure campaign effectiveness.","investor.nvidia.com","This cookie is associated with Eventbrite and is used to deliver content tailored to the end user's interests and improve content creation. This cookie is also used for event-booking purposes.","_gat_gtag_UA_140825383_2","Google Analytics","_rdt_uuid","This cookie is set by Reddit and is used for tracking the views of embedded videos and performance of the advertisements.","catalog.ngc.nvidia.com","_uetsid","This cookie is used by Bing to determine what ads should be shown that may be relevant to the end user perusing the site. ","kndctr_F207D74D549850760A4C98C6_AdobeOrg_bc_session_id","ttcsid_XXXXXXXXXXXXXXXXXXXXCategory","This cookie name is associated with TikTok which is used to track your activity on the platform, including how you interact with their embedded services on other websites.This cookie is associated with TikTok. It helps track your activity on the platform, including how you interact with their embedded services on other websites.","_fbp","Used by Facebook to deliver a series of advertisement products such as real time bidding from third party advertisers","_zitok","_twpid","This cookie is typically associated with the use of Taptap Digital, a company specializing in digital advertising. It is used for tracking and ad personalization purposes.","_tt_enable_cookie","This cookie name is associated with TikTok which is used to collect data about behavior and purchases on the website and to measure the effect of advertising. 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It helps track your activity on the platform, including how you interact with their embedded services on other websites.","C0003","Personalization Cookies","These cookies collect data about how you have interacted with our website to help us improve your web experience, such as which pages you have visited. These cookies may store a unique ID so that our system will remember you when you return. They may be set by us or by third party providers whose services we have added to our pages. These cookies enable us to provide enhanced website functionality and personalization as well as make the marketing messages we send to you more relevant to your interests. If you do not allow these cookies, then some or all of these services may not function properly.",4,[610,611,612,613,614,615,616,617,618,619,620,621,622,623,624,625,626,627,628,629,630,631,632,633,634],[581,582,583,584,585],{"_419":494,"_252":494,"_219":226,"_392":605},{"_419":468,"_252":468,"_219":226,"_392":600},{"_419":595,"_252":595,"_219":226,"_392":596},{"_419":590,"_252":590,"_219":226,"_392":591},{"_419":586,"_252":586,"_219":226,"_392":587},"nvidia.partners",[588],{"_115":589,"_425":586,"_426":35,"_219":462},"edge","app.hushly.com",[592],{"_115":593,"_425":590,"_426":35,"_219":594},"*CORS","This domain is associated with Hushly, a platform that provides lead conversion solutions for content marketing by using personalization and content engagement strategies.","github.com",[597],{"_115":598,"_425":595,"_426":35,"_219":599},"_octo","This domain is owned by Github. 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These cookies may store a unique ID so that our system will remember you when you return. Information collected with these cookies is used to measure and find ways to improve website performance.",[693,694,695,696,697,698,699,700,701,702,703,704,705,706,707,708,709,710,711,712,713,714,715,716,717,718,719,720,721],[673,674,675,676],{"_419":688,"_252":688,"_219":226,"_392":689},{"_419":683,"_252":683,"_219":226,"_392":684},{"_419":481,"_252":481,"_219":226,"_392":680},{"_419":595,"_252":595,"_219":226,"_392":677},[678],{"_115":679,"_425":595,"_426":90,"_219":599},"_gh_sess",[681],{"_115":682,"_425":481,"_426":90,"_219":488},"YSC","bizible.com",[685],{"_115":686,"_425":683,"_426":35,"_219":687},"_BUID","Bizible is a marketing attribution software that tracks the performance of marketing efforts and connects them to revenue, primarily used for B2B environments.","a.usbrowserspeed.com",[690],{"_115":691,"_425":688,"_426":35,"_219":692},"tuid","This domain is owned by Ookla which provides internet speed testing services through its Speedtest application.",{"_115":763,"_425":540,"_426":35,"_219":764},{"_115":748,"_425":762,"_426":90,"_219":749},{"_115":731,"_425":543,"_426":35,"_219":656},{"_115":731,"_425":644,"_426":35,"_219":656},{"_115":760,"_425":540,"_426":35,"_219":761},{"_115":748,"_425":546,"_426":90,"_219":749},{"_115":758,"_425":540,"_426":35,"_219":759},{"_115":748,"_425":543,"_426":90,"_219":749},{"_115":756,"_425":643,"_426":35,"_219":757},{"_115":748,"_425":665,"_426":90,"_219":749},{"_115":728,"_425":543,"_426":35,"_219":730},{"_115":754,"_425":540,"_426":90,"_219":755},{"_115":752,"_425":540,"_426":35,"_219":753},{"_115":750,"_425":540,"_426":90,"_219":751},{"_115":748,"_425":639,"_426":90,"_219":749},{"_115":746,"_425":540,"_426":35,"_219":747},{"_115":744,"_425":540,"_426":35,"_219":745},{"_115":742,"_425":540,"_426":90,"_219":743},{"_115":740,"_425":648,"_426":35,"_219":741},{"_115":728,"_425":639,"_426":35,"_219":730},{"_115":738,"_425":540,"_426":35,"_219":739},{"_115":736,"_425":540,"_426":90,"_219":737},{"_115":734,"_425":540,"_426":35,"_219":735},{"_115":732,"_425":540,"_426":35,"_219":733},{"_115":731,"_425":540,"_426":35,"_219":656},{"_115":728,"_425":729,"_426":35,"_219":730},{"_115":726,"_425":540,"_426":35,"_219":727},{"_115":724,"_425":540,"_426":90,"_219":725},{"_115":722,"_425":540,"_426":35,"_219":723},"_ga_xxxxxxxxxx","Used by Google Analytics to identify and track an individual session with your device.","s_ppvl","This cookie is set by Adobe Analytics to store information on the percentage of the page displayed to the end user.","coveo_visitorId","This cookie name is associated with Coveo which is used to store a unique user ID for marketing purposes and to track the number of distinct users who submitted a query or clicked an item, counting them only once even if they did the same query or clicked the same item over the course of many visits.","_dd_s","marketplace.nvidia.com","Datadog Cookie used to group all events generated from a unique user session across multiple pages. 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	Files	Compressed Size
3	16	14.49 GB	September 4, 2024 UTC
2Selected	16	13.94 GB	October 17, 2023 UTC
1	16	13.94 GB	April 19, 2023 UTC