cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5215919
title: EAW FASTQ files for bioinformatic courses (18S rRNA genes, 2018)

description: Selection of 6 samples, with 6 Forward (R1) and 6 Reverse (R2) files, including primers. R1 and R2 reads are ca. 300 bp long, and were obtained from Illumina MiSeq technologies, at the FEM facility sequencing platform. The files refer to the18S rRNA gene reads obtained from the analyses carried out on the samples collected and filtered (Sterivex<sup>TM</sup> 0.22 µm) in different areas and depths of Lake Garda on September, 2018 (see EAW_2018_FASTQ_18S_description.docx). Sampling and analyses were carried out in the framework of the project Eco-AlpsWater (ASP569), funded by the Interreg Alpine Space program. A bioinformatic protocol for analyzing these data using DADA2 is available in Zenodo: <pre>https://doi.org/10.5281/zenodo.5233527</pre> The corresponding 16S rRNA gene reads, obtained from the same eDNA extracts, are saved in https://doi.org/10.5281/zenodo.5215815
DOI: 10.5281/zenodo.5215918
title: EAW FASTQ files for bioinformatic courses (18S rRNA genes, 2018)

description: Selection of 6 samples, with 6 Forward (R1) and 6 Reverse (R2) files, including primers. R1 and R2 reads are ca. 300 bp long, and were obtained from Illumina MiSeq technologies, at the FEM facility sequencing platform. The files refer to the18S rRNA gene reads obtained from the analyses carried out on the samples collected and filtered (Sterivex<sup>TM</sup> 0.22 µm) in different areas and depths of Lake Garda on September, 2018 (see EAW_2018_FASTQ_18S_description.docx). Sampling and analyses were carried out in the framework of the project Eco-AlpsWater (ASP569), funded by the Interreg Alpine Space program. A bioinformatic protocol for analyzing these data using DADA2 is available in Zenodo: <pre>https://doi.org/10.5281/zenodo.5233527</pre> The corresponding 16S rRNA gene reads, obtained from the same eDNA extracts, are saved in https://doi.org/10.5281/zenodo.5215815
DOI: 10.5281/zenodo.5361958
title: Precomputation of Image Features for the Classification of Dynamic Properties in Waves

description: Image data and H5 files from feature extraction too large for Github related to the project Precomputation of Image Features for the Classification of Dynamic Properties in Waves.
DOI: 10.5281/zenodo.5361957
title: Precomputation of Image Features for the Classification of Dynamic Properties in Waves

description: Image data and H5 files from feature extraction too large for Github related to the project Precomputation of Image Features for the Classification of Dynamic Properties in Waves.
DOI: 10.6084/m9.figshare.16554015
title: Data_Figure 11.txt

description: Data presented in figure 11
DOI: 10.6084/m9.figshare.16554033.v1
title: Data_Figure 9

description: Data presented in figure 9
DOI: 10.6084/m9.figshare.16554033
title: Data_Figure 9

description: Data presented in figure 9
DOI: 10.6084/m9.figshare.16554012
title: Data_Figure 10.txt

description: Data presented in figure 10
DOI: 10.6084/m9.figshare.16554012.v1
title: Data_Figure 10.txt

description: Data presented in figure 10
DOI: 10.6084/m9.figshare.14166467
title: Rostral morphology of Spinosauridae (Theropoda, Megalosauroidea): premaxilla shape variation and a new phylogenetic inference

description: Supplemental online materials for: <br>Lacerda, Grillo, & Romano (2021). <b>Rostral morphology of Spinosauridae (Theropoda, Megalosauroidea): premaxilla shape variation and a new phylogenetic inference</b>. Historical Biology.<br><b><i>Data files</i></b><br><b><i><sub><br></sub></i></b> <b><i> </i></b> <b>GMM data</b>. Matrices with LMs coordinates; Procrustes coordinates, analysis and results of ordination methods and multivariate regression. <b> </b> <b><br></b><b>CAC data</b>. Matrices with LMs coordinates corrected by Common Allometric Component analysis. <b> </b> <b><br></b><b>PM data</b>. Phylogenetic Morphometrics matrix combining standard characters and premaxillae configurations.
DOI: 10.6084/m9.figshare.16554018
title: Rawdata_Figure 6.txt

description: Data presented in figure 6
DOI: 10.6084/m9.figshare.16554018.v1
title: Rawdata_Figure 6.txt

description: Data presented in figure 6
DOI: 10.6084/m9.figshare.14974920.v5
title: CAN THE FINANCIAL PERFORMANCE OF THE MICRO, SMALL AND MEDIUM-SIZED ENTERPRISE PRODUCTION SECTOR IN MEDAN BE A SIGNAL IN THE USE OF A LEANNESS STRATEGY?

description: This project contains the following underlying data: Data file 1. (Map of Medan City with its 21 Districts (Kecamatan)); Data file 2. (Figure of Path Diagram from The Final Bootstrapping); Data file 3. (Final Path Coefficient); Data file 4. (Final Outer Loadings); Data file 5. (The Third (Final) Bootstrapping Result); Data file 6. (Validation and Reliability Result); Data file 7. (Dataset for Questionnaire Validation & Reliability (49 Respondents)); Data file 8. (Intercorrelation Testing Result); Data file 9. (E-Questionnaire on Google Form); Data file 10. (Research Questionnaire); Data file 11. (Dataset of Leanness Strategy of Medan Micro & SMEs (169 Respondents)); Data file 12. (466 business actors of Targeting Population); Data file 13 (Path Coefficient - Explanation for exclusion Hypothesis 3, Hypothesis 5, Hypothesis 6, and Hypothesis 7).Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).<br><br>
DOI: 10.6084/m9.figshare.16554039
title: Dataset

description: Data presented in figures 6, 9, 10, and 11
DOI: 10.6084/m9.figshare.14974920
title: CAN THE FINANCIAL PERFORMANCE OF THE MICRO, SMALL AND MEDIUM-SIZED ENTERPRISE PRODUCTION SECTOR IN MEDAN BE A SIGNAL IN THE USE OF A LEANNESS STRATEGY?

description: This project contains the following underlying data: Data file 1. (Map of Medan City with its 21 Districts (Kecamatan)); Data file 2. (Figure of Path Diagram from The Final Bootstrapping); Data file 3. (Final Path Coefficient); Data file 4. (Final Outer Loadings); Data file 5. (The Third (Final) Bootstrapping Result); Data file 6. (Validation and Reliability Result); Data file 7. (Dataset for Questionnaire Validation & Reliability (49 Respondents)); Data file 8. (Intercorrelation Testing Result); Data file 9. (E-Questionnaire on Google Form); Data file 10. (Research Questionnaire); Data file 11. (Dataset of Leanness Strategy of Medan Micro & SMEs (169 Respondents)); Data file 12. (Groups in the Production Sector of 466 businesses); Data file 13 (Path Coefficient - Explanation for exclusion Hypothesis 3, Hypothesis 5, Hypothesis 6, and Hypothesis 7).Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).<br><br>
DOI: 10.6084/m9.figshare.14974920.v7
title: CAN THE FINANCIAL PERFORMANCE OF THE MICRO, SMALL AND MEDIUM-SIZED ENTERPRISE PRODUCTION SECTOR IN MEDAN BE A SIGNAL IN THE USE OF A LEANNESS STRATEGY?

description: This project contains the following underlying data: Data file 1. (Map of Medan City with its 21 Districts (Kecamatan)); Data file 2. (Figure of Path Diagram from The Final Bootstrapping); Data file 3. (Final Path Coefficient); Data file 4. (Final Outer Loadings); Data file 5. (The Third (Final) Bootstrapping Result); Data file 6. (Validation and Reliability Result); Data file 7. (Dataset for Questionnaire Validation & Reliability (49 Respondents)); Data file 8. (Intercorrelation Testing Result); Data file 9. (E-Questionnaire on Google Form); Data file 10. (Research Questionnaire); Data file 11. (Dataset of Leanness Strategy of Medan Micro & SMEs (169 Respondents)); Data file 12. (Groups in the Production Sector of 466 businesses); Data file 13 (Path Coefficient - Explanation for exclusion Hypothesis 3, Hypothesis 5, Hypothesis 6, and Hypothesis 7).Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).<br><br>
DOI: 10.6084/m9.figshare.14974920.v6
title: CAN THE FINANCIAL PERFORMANCE OF THE MICRO, SMALL AND MEDIUM-SIZED ENTERPRISE PRODUCTION SECTOR IN MEDAN BE A SIGNAL IN THE USE OF A LEANNESS STRATEGY?

description: This project contains the following underlying data: Data file 1. (Map of Medan City with its 21 Districts (Kecamatan)); Data file 2. (Figure of Path Diagram from The Final Bootstrapping); Data file 3. (Final Path Coefficient); Data file 4. (Final Outer Loadings); Data file 5. (The Third (Final) Bootstrapping Result); Data file 6. (Validation and Reliability Result); Data file 7. (Dataset for Questionnaire Validation & Reliability (49 Respondents)); Data file 8. (Intercorrelation Testing Result); Data file 9. (E-Questionnaire on Google Form); Data file 10. (Research Questionnaire); Data file 11. (Dataset of Leanness Strategy of Medan Micro & SMEs (169 Respondents)); Data file 12. (Groups in the Production Sector of 466 businesses); Data file 13 (Path Coefficient - Explanation for exclusion Hypothesis 3, Hypothesis 5, Hypothesis 6, and Hypothesis 7).Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).<br><br>
DOI: 10.5281/zenodo.5356840
title: Data acquired by Agrob V1X @UTAD

description: <strong>DS_AG_29</strong> Data acquired by Agrob V16 @UTAD<br> (10 seconds bag with 130 frames)<br> - Monocular Camera<br> - Depth Camera (Kinect)<br> - RGB Camera (Kinect)<br> - Laser Scan test_ground_truth_10_sec.bag / 642Mb / ROSBag <strong>DS_AG_32</strong> Data acquired by Agrob V14 @UTAD<br> - IMU<br> - Monocular Camera<br> - Raw Data Sensors<br> - Power State 2017-10-04_17-50_agrobv14_utad.bag / 174Mb / ROSBag
DOI: 10.5281/zenodo.5356839
title: Data acquired by Agrob V1X @UTAD

description: <strong>DS_AG_29</strong> Data acquired by Agrob V16 @UTAD<br> (10 seconds bag with 130 frames)<br> - Monocular Camera<br> - Depth Camera (Kinect)<br> - RGB Camera (Kinect)<br> - Laser Scan test_ground_truth_10_sec.bag / 642Mb / ROSBag <strong>DS_AG_32</strong> Data acquired by Agrob V14 @UTAD<br> - IMU<br> - Monocular Camera<br> - Raw Data Sensors<br> - Power State 2017-10-04_17-50_agrobv14_utad.bag / 174Mb / ROSBag
DOI: 10.5281/zenodo.5362354
title: Vine Trunk Image/Annotation Dataset

description: <strong>DS_AG_39</strong> VineSet - Vine Trunk Image/Annotation Dataset<br> - RGB images<br> - Thermal images<br> - Infrablue filtered images<br> vineset.zip / 1.1Gb / Images and Annotations
DOI: 10.5281/zenodo.5359536
title: Data acquired by Agrob V16 @ Sogrape / FEUP / UTAD

description: <strong>DS_RM_02</strong> Data acquired by Agrob V16 @Sogrape<br> (16/10/2017 de tarde)- /camera/camera_info<br> - /camera/image_raw/compressed<br> - /gps/fix<br> - /gps/time<br> - /husky_velocity_controller/odm<br> - /lidar1/lidar1/parameter_updates<br> - /lidar1/scan<br> - /map<br> - /map_metadata<br> - /map_ndvi_py<br> - /odometry/filtered<br> - /pcl_v<br> - /poseupdate<br> - /pozyxAccel<br> - /pozyxEuler<br> - /pozyxGrav<br> - /pozyxIMU<br> - /pozyxMagn<br> - /pozyxPose<br> - /pozyxPressure<br> - /pozyxRange<br> - /pozyxTemp<br> - /projected_map<br> - /scan<br> - /tf 01_tarde_sogrape.bag / 1.0Gb / ROSBag <strong>DS_RM_03</strong> Data acquired by Agrob V16 @Sogrape<br> (16/10/2017 de tarde)- /camera/camera_info<br> - /gps/fix<br> - /gps/time<br> - /husky_velocity_controller/odm<br> - /lidar1/lidar1/parameter_updates<br> - /lidar1/scan<br> - /map<br> - /map_metadata<br> - /map_ndvi_py<br> - /odometry/filtered<br> - /pcl_v<br> - /poseupdate<br> - /pozyxAccel<br> - /pozyxEuler<br> - /pozyxGrav<br> - /pozyxIMU<br> - /pozyxMagn<br> - /pozyxPose<br> - /pozyxPressure<br> - /pozyxRange<br> - /pozyxTemp<br> - /projected_map<br> - /scan<br> - /tf 02_tarde_sogrape.bag / 8.9Gb / ROSBag <strong>DS_RM_04</strong> Data acquired by Agrob V16 @Sogrape<br> (13/11/2017 de tarde) - All bag_sogrape_1.bag / 3.3Gb / ROSBag <strong>DS_RM_05</strong> Data acquired by Agrob V16 @Sogrape<br> (13/11/2017 de tarde)- /camera/image_raw/compressed<br> - /pozyxPose<br> - /pozyxRange<br> - lidar1/scan<br> - map<br> - scan<br> - tf bag_sogrape_2.bag / 1.1Gb / ROSBag <strong>DS_RM_06</strong> Data acquired by Agrob V16 @FEUP_i109<br> (03/04/2018 de manhã)<br> - /imu_um7/data<br> - /imu_um7/mag<br> - /imu_um7/temperature<br> - map<br> - tf imu_um7.bag / 44.6 Mb / ROSBag <br> <strong>DS_RM_07</strong> Data acquired by Agrob V16 @FEUP_i109<br> (03/04/2018 de manhã (mais dados))<br> - /imu_um7/data<br> - /imu_um7/temperature<br> - /poseupdate<br> - /slam_out_pose<br> - /odometry/filtered<br> - map<br> - tf imu_um7.bag / 30.2 Mb / ROSBag <br> <strong>DS_RM_08</strong> Data acquired by Agrob V16 @FEUP_i109<br> (03/04/2018 de manhã (mais dados))<br> - /imu_um7/data<br> - /imu_um7/mag<br> - /imu_um7/temperature<br> - /imu_um7/rpy<br> - /poseupdate<br> - /slam_out_pose<br> - /odometry/filtered<br> - map<br> - tf imu_um7_3.bag / Csv_data / 15.0 Mb / ROSBag 198.5 kB / CSV <strong>DS_RM_09</strong> Data acquired by Agrob V16 @UTAD (20/04/2018)<br> - /husky_velocity_controller/cmd_vel<br> - /husky_velocity_controller/odom<br> - /image_raw/compressed<br> - /imu_um7/rpy<br> - /poseupdate<br> - /imu_to_tf_node/RPY<br> - /odometry/filtered<br> - /imu_to_tf_node/RPY<br> - /imu_um7/mag<br> - /imu_um7/rpy<br> - /imu_um7/temperature<br> - /lidar1/scan<br> - /map<br> - /map_metadata<br> - /octomap_binary<br> - /octomap_full<br> - /octomap_point_cloud_centers<br> - /odometry/filtered<br> - /scan<br> - /slam_out_pose<br> - tf UTAD.bag / 5 GB / ROSBag
DOI: 10.5281/zenodo.5357239
title: Data acquired by Agrob V18 @Places

description: <strong>DS_AG_33</strong> Data acquired by Agrob V18 @INESCTEC<br> - Point Cloud (Velodyne Puck 16)<br> - Thermal Camera (Flir m232)<br> - IMU<br> agrobv18_feup1.bag / agrobv18_feup2.bag / 4.4Gb / 1.9Gb / ROSBag <strong>DS_AG_34</strong> Data acquired by Agrob V18 @LOBÃO<br> - Point Cloud (Velodyne Puck 16)<br> - Thermal Camera (Flir m232)<br> - IMU<br> - GNSS<br> - Hokuyo Laser Scan<br> Agrob_V18_2019-03-08-11-46-02.bag.tar.gz / Agrob_V18_2019-03-08-11-59-18.bag / 3.7Gb / ROSBag(compressed) 1.3Gb / ROSBag <strong>DS_AG_35</strong> Data acquired by Agrob V18 @Vila do Conde<br> - Point Cloud (Velodyne Puck 16)<br> - IMU<br> - GNSS<br> - Hokuyo Laser Scan<br> Agrob_V18_2019-04-30-VilaConde.zip / 3.2Gb / ROSBag(compressed) <strong>DS_AG_36</strong> Data acquired by Agrob V18 [Husky base] @Figueiredo - Braga<br> - Point Cloud (Velodyne Puck 16)<br> - IMU<br> - GNSS<br> - Hokuyo Laser Scan<br> - ZED<br> Figueiredo_Agrob_V18_2019-06-25.zip / 5.8Gb / ROSBag(compressed) <strong>DS_AG_37</strong> Data acquired by Agrob V18 [Husky base] @Quinta do Seixo - Pinhão<br> - Point Cloud (Velodyne Puck 16)<br> - IMU<br> - GNSS<br> - Hokuyo Laser Scan<br> - ZED<br> Agrob_V18_2019-07-31-Seixo1.bag.zip / Agrob_V18_2019-07-31-Seixo2.bag.zip /Agrob_V18_2019-07-31-Seixo3.zip<br> 3.4Gb / ROSBag(compressed)<br> 6.1Gb / ROSBag(compressed)<br> 4.8Gb / ROSBag(compressed)
DOI: 10.5281/zenodo.5362353
title: Vine Trunk Image/Annotation Dataset

description: <strong>DS_AG_39</strong> VineSet - Vine Trunk Image/Annotation Dataset<br> - RGB images<br> - Thermal images<br> - Infrablue filtered images<br> vineset.zip / 1.1Gb / Images and Annotations
DOI: 10.5281/zenodo.5359535
title: Data acquired by Agrob V16 @ Sogrape / FEUP / UTAD

description: <strong>DS_RM_02</strong> Data acquired by Agrob V16 @Sogrape<br> (16/10/2017 de tarde)- /camera/camera_info<br> - /camera/image_raw/compressed<br> - /gps/fix<br> - /gps/time<br> - /husky_velocity_controller/odm<br> - /lidar1/lidar1/parameter_updates<br> - /lidar1/scan<br> - /map<br> - /map_metadata<br> - /map_ndvi_py<br> - /odometry/filtered<br> - /pcl_v<br> - /poseupdate<br> - /pozyxAccel<br> - /pozyxEuler<br> - /pozyxGrav<br> - /pozyxIMU<br> - /pozyxMagn<br> - /pozyxPose<br> - /pozyxPressure<br> - /pozyxRange<br> - /pozyxTemp<br> - /projected_map<br> - /scan<br> - /tf 01_tarde_sogrape.bag / 1.0Gb / ROSBag <strong>DS_RM_03</strong> Data acquired by Agrob V16 @Sogrape<br> (16/10/2017 de tarde)- /camera/camera_info<br> - /gps/fix<br> - /gps/time<br> - /husky_velocity_controller/odm<br> - /lidar1/lidar1/parameter_updates<br> - /lidar1/scan<br> - /map<br> - /map_metadata<br> - /map_ndvi_py<br> - /odometry/filtered<br> - /pcl_v<br> - /poseupdate<br> - /pozyxAccel<br> - /pozyxEuler<br> - /pozyxGrav<br> - /pozyxIMU<br> - /pozyxMagn<br> - /pozyxPose<br> - /pozyxPressure<br> - /pozyxRange<br> - /pozyxTemp<br> - /projected_map<br> - /scan<br> - /tf 02_tarde_sogrape.bag / 8.9Gb / ROSBag <strong>DS_RM_04</strong> Data acquired by Agrob V16 @Sogrape<br> (13/11/2017 de tarde) - All bag_sogrape_1.bag / 3.3Gb / ROSBag <strong>DS_RM_05</strong> Data acquired by Agrob V16 @Sogrape<br> (13/11/2017 de tarde)- /camera/image_raw/compressed<br> - /pozyxPose<br> - /pozyxRange<br> - lidar1/scan<br> - map<br> - scan<br> - tf bag_sogrape_2.bag / 1.1Gb / ROSBag <strong>DS_RM_06</strong> Data acquired by Agrob V16 @FEUP_i109<br> (03/04/2018 de manhã)<br> - /imu_um7/data<br> - /imu_um7/mag<br> - /imu_um7/temperature<br> - map<br> - tf imu_um7.bag / 44.6 Mb / ROSBag <br> <strong>DS_RM_07</strong> Data acquired by Agrob V16 @FEUP_i109<br> (03/04/2018 de manhã (mais dados))<br> - /imu_um7/data<br> - /imu_um7/temperature<br> - /poseupdate<br> - /slam_out_pose<br> - /odometry/filtered<br> - map<br> - tf imu_um7.bag / 30.2 Mb / ROSBag <br> <strong>DS_RM_08</strong> Data acquired by Agrob V16 @FEUP_i109<br> (03/04/2018 de manhã (mais dados))<br> - /imu_um7/data<br> - /imu_um7/mag<br> - /imu_um7/temperature<br> - /imu_um7/rpy<br> - /poseupdate<br> - /slam_out_pose<br> - /odometry/filtered<br> - map<br> - tf imu_um7_3.bag / Csv_data / 15.0 Mb / ROSBag 198.5 kB / CSV <strong>DS_RM_09</strong> Data acquired by Agrob V16 @UTAD (20/04/2018)<br> - /husky_velocity_controller/cmd_vel<br> - /husky_velocity_controller/odom<br> - /image_raw/compressed<br> - /imu_um7/rpy<br> - /poseupdate<br> - /imu_to_tf_node/RPY<br> - /odometry/filtered<br> - /imu_to_tf_node/RPY<br> - /imu_um7/mag<br> - /imu_um7/rpy<br> - /imu_um7/temperature<br> - /lidar1/scan<br> - /map<br> - /map_metadata<br> - /octomap_binary<br> - /octomap_full<br> - /octomap_point_cloud_centers<br> - /odometry/filtered<br> - /scan<br> - /slam_out_pose<br> - tf UTAD.bag / 5 GB / ROSBag
DOI: 10.5281/zenodo.5356368
title: Data acquired by ... @Agrob Simulator

description: <strong>DS_AG_24</strong> - Data acquired by ... @Agrob Simulator (Gazebo 2 levels) - IMU<br> - Odometry<br> - Laser Scan<br> - CmdVel<br> - Gazebo 2015-01-15-19-39-42.bag / 711Mb / ROSBag <strong>DS_AG_25</strong> Data acquired by ... @Agrob Simulator<br> (Gazebo vineyard first line)<br> - Odometry<br> - Laser Scan<br> - Camera (RGB/IR)<br> - CmdVel<br> - Gazebo<br> - Waypoints Gazebo_vineyard_first_line.bag/ 4Gb / ROSBag
DOI: 10.5281/zenodo.5084587
title: Agrob V16 Data Acquisition @INESCTEC-FEUP

description: <strong>DS_AG_13</strong> - Data acquired by Agrob V16 @FEUP-INESCTEC<br> - Odometry<br> - TF<br> - Pozyx (Range)<br> - Antenna (iBeacon) -2017-04-11-16-37-16.bag / 38Mb / ROSBag <br> <strong>DS_AG_14</strong> - Data acquired by Agrob V16 @FEUP-INESCTEC<br> - Odometry<br> - TF<br> - Pozyx (Range)<br> - Antenna (iBeacon) 2017-04-11-16-43-21.bag / 3.5Mb / ROSBag <br> <strong>DS_AG_15</strong> - Data acquired by Agrob V16 @FEUP-INESCTEC<br> - Odometry<br> - TF<br> - Pozyx (Range)<br> - Antenna (iBeacon) 2017-04-11-16-43-46.bag / 105Mb / ROSBag <br> <strong>DS_AG_16 - </strong>Data acquired by Agrob V16 @FEUP-INESCTEC<br> - Laser Scan<br> - Odometry<br> - TF<br> - Pozyx (Pose/Range)<br> - Antenna (iBeacon) 2017-04-11-17-20-35.bag.active / 164Mb / ROSBag <br> <strong>DS_AG_17 - </strong>Data acquired by Agrob V16 @FEUP-INESCTEC<br> - Laser Scan<br> - GPS<br> - Odometry<br> - TF<br> - Pozyx (Pose/Range/IMU)<br> - Antenna (iBeacon) 2017-05-19-16-50-42.bag / 262Mb / ROSBag <br> <strong>DS_AG_18 - </strong>Data acquired by Agrob V16 @INESCTEC<br> - Laser Scan<br> - Odometry<br> - TF<br> - Pozyx (Range/Pose/IMU/Temp/Pressure/Magn/Euler/Accel)<br> - Antenna (iBeacon) 2017-05-30-17-54-02.bag / 258Mb / ROSBag <br> <strong>DS_AG_19 - </strong>Data acquired by Agrob V16 @INESCTEC<br> - Laser Scan<br> - Monocular Camera<br> - Odometry<br> - TF<br> - Pozyx (Range/Pose/IMU/Temp/Pressure/Magn/Euler/Accel)<br> - Antenna (iBeacon) 2017-05-30-18-09-05.bag / 14Mb / ROSB <strong>DS_AG_20</strong> - Data acquired by Agrob V16 @INESCTEC<br> - Laser Scan<br> - Monocular Camera<br> - Odometry<br> - TF<br> - Pozyx (Range/Pose/IMU/Temp/Pressure/Magn/Euler/Accel)<br> - Antenna (iBeacon) 2017-05-30-18-09-11.bag / 2.5Gb / ROSBag <br> <strong>DS_AG_21 - </strong>Data acquired by Agrob V16 @INESCTEC<br> - Laser Scan<br> - Odometry<br> - TF<br> - Pozyx (Range/Pose/IMU/Temp/Pressure/Magn/Euler/Accel)<br> - Antenna (iBeacon) 2017-05-30-18-17-47.bag / 181Mb / ROSBag <br> <strong>DS_AG_22 - </strong>Data acquired by Agrob V14 @INESCTEC<br> - IBeacons<br> - IMU<br> - GPS (Wrong)<br> - Monocular Camera<br> - Laser Scan (Partial)<br> - Raw Data Sensors<br> - Power State<br> - CmdVelI BeaconsTeste_29_junho_2015.bag / 415Mb / ROSBag <br> <strong>DS_AG_23 - </strong>Data acquired by Agrob V16 @INESCTEC<br> - Odometry (Without variation)<br> - Antenna (iBeacon) dados_2017_03_14.bag / 169Kb / ROSBag
DOI: 10.5281/zenodo.5357238
title: Data acquired by Agrob V18 @Places

description: <strong>DS_AG_33</strong> Data acquired by Agrob V18 @INESCTEC<br> - Point Cloud (Velodyne Puck 16)<br> - Thermal Camera (Flir m232)<br> - IMU<br> agrobv18_feup1.bag / agrobv18_feup2.bag / 4.4Gb / 1.9Gb / ROSBag <strong>DS_AG_34</strong> Data acquired by Agrob V18 @LOBÃO<br> - Point Cloud (Velodyne Puck 16)<br> - Thermal Camera (Flir m232)<br> - IMU<br> - GNSS<br> - Hokuyo Laser Scan<br> Agrob_V18_2019-03-08-11-46-02.bag.tar.gz / Agrob_V18_2019-03-08-11-59-18.bag / 3.7Gb / ROSBag(compressed) 1.3Gb / ROSBag <strong>DS_AG_35</strong> Data acquired by Agrob V18 @Vila do Conde<br> - Point Cloud (Velodyne Puck 16)<br> - IMU<br> - GNSS<br> - Hokuyo Laser Scan<br> Agrob_V18_2019-04-30-VilaConde.zip / 3.2Gb / ROSBag(compressed) <strong>DS_AG_36</strong> Data acquired by Agrob V18 [Husky base] @Figueiredo - Braga<br> - Point Cloud (Velodyne Puck 16)<br> - IMU<br> - GNSS<br> - Hokuyo Laser Scan<br> - ZED<br> Figueiredo_Agrob_V18_2019-06-25.zip / 5.8Gb / ROSBag(compressed) <strong>DS_AG_37</strong> Data acquired by Agrob V18 [Husky base] @Quinta do Seixo - Pinhão<br> - Point Cloud (Velodyne Puck 16)<br> - IMU<br> - GNSS<br> - Hokuyo Laser Scan<br> - ZED<br> Agrob_V18_2019-07-31-Seixo1.bag.zip / Agrob_V18_2019-07-31-Seixo2.bag.zip /Agrob_V18_2019-07-31-Seixo3.zip<br> 3.4Gb / ROSBag(compressed)<br> 6.1Gb / ROSBag(compressed)<br> 4.8Gb / ROSBag(compressed)