Data

Ground vehicle approaching negative obstacles

Commonwealth Scientific and Industrial Research Organisation
Hines, Tom ; Stepanas, Kazys ; Talbot, Fletcher ; Sa, Inkyu ; Lewis, Jake ; Hernandez, Emili ; Kottege, Navinda ; Hudson, Nicolas
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/8q8g-6y10&rft.title=Ground vehicle approaching negative obstacles&rft.identifier=https://doi.org/10.25919/8q8g-6y10&rft.publisher=Commonwealth Scientific and Industrial Research Organisation&rft.description=ROS pointcloud and odometry streams recorded during various scenarios where a robotic ground vehicle approaches negative obstacles. These values were generated by the Wildcat SLAM software based on measurements by a Velodyne lidar and an IMU. Often negative obstacles cannot be observed directly by a ground vehicle as they are obscured by the upper surface between the vehicle and the obstacle. This data contains examples that can be used to demonstrate methods of indirectly inferring negative obstacles from typical observations made during an approach. Screenshot image previews of the data can be found in the `screenshots` directory. ROS topics are described in the `README.md` file. Models of the simulation worlds have been provided as Blender files in the `worlds` directory.Lineage: This data was collected by one of the robots built by the CSIRO Data61 DARPA SubT Challenge team. Some of this data was recorded while the robot was moving autonomously and some of it was recorded while the robot was being teleoperated by a human.&rft.creator=Hines, Tom &rft.creator=Stepanas, Kazys &rft.creator=Talbot, Fletcher &rft.creator=Sa, Inkyu &rft.creator=Lewis, Jake &rft.creator=Hernandez, Emili &rft.creator=Kottege, Navinda &rft.creator=Hudson, Nicolas &rft.date=2021&rft.edition=v2&rft.relation=https://arxiv.org/abs/2010.16018&rft_rights=Creative Commons Attribution 4.0 International Licence https://creativecommons.org/licenses/by/4.0/&rft_rights=Data is accessible online and may be reused in accordance with licence conditions&rft_rights=All Rights (including copyright) CSIRO 2021.&rft_subject=robotics&rft_subject=Field robotics&rft_subject=Control engineering, mechatronics and robotics&rft_subject=ENGINEERING&rft.type=dataset&rft.language=English Access the data

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Creative Commons Attribution 4.0 International Licence
https://creativecommons.org/licenses/by/4.0/

Data is accessible online and may be reused in accordance with licence conditions

All Rights (including copyright) CSIRO 2021.

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ROS pointcloud and odometry streams recorded during various scenarios where a robotic ground vehicle approaches negative obstacles. These values were generated by the Wildcat SLAM software based on measurements by a Velodyne lidar and an IMU. Often negative obstacles cannot be observed directly by a ground vehicle as they are obscured by the upper surface between the vehicle and the obstacle. This data contains examples that can be used to demonstrate methods of indirectly inferring negative obstacles from typical observations made during an approach. Screenshot image previews of the data can be found in the `screenshots` directory. ROS topics are described in the `README.md` file. Models of the simulation worlds have been provided as Blender files in the `worlds` directory.
Lineage: This data was collected by one of the robots built by the CSIRO Data61 DARPA SubT Challenge team. Some of this data was recorded while the robot was moving autonomously and some of it was recorded while the robot was being teleoperated by a human.

Available: 2021-01-21

Data time period: 2020-09-08 to 2021-01-13

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ACN 633 798 857