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{
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{
            
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  "author": "Jeldrik Axmann, Rozhin Moftizadeh, Jingyao Su, Benjamin 
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  "author": "Jeldrik Axmann",
            
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Tennstedt, Qianqian Zou, Yunshuang Yuan, Dominik Ernst, Hamza 

            
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Alkhatib, Claus Brenner, Steffen Sch\u00f6n",

            
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  "author_email": "jeldrik.axmann@ikg.uni-hannover.de",
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  "author_email": "jeldrik.axmann@ikg.uni-hannover.de",
            
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            
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  "doi": "10.25835/75o9yrc0",
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  "doi": "10.25835/75o9yrc0",
            
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  "doi_date_published": "2023-01-16",
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  "doi_date_published": "2023-01-16",
            
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  "doi_publisher": "LUIS",
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  "doi_publisher": "LUIS",
            
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  "doi_status": "true",
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  "doi_status": "true",
            
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  "domain": "https://data.uni-hannover.de",
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  "domain": "https://data.uni-hannover.de",
            
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  "extra_authors": [
            
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    {
            
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      "extra_author": " Rozhin Moftizadeh"
            
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    },
            
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    {
            
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      "extra_author": " Jingyao Su"
            
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    },
            
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    {
            
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      "extra_author": " Benjamin Tennstedt"
            
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    },
            
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    {
            
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      "extra_author": " Qianqian Zou"
            
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    },
            
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    {
            
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      "extra_author": " Yunshuang Yuan"
            
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    },
            
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    {
            
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      "extra_author": " Dominik Ernst"
            
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    },
            
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    {
            
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      "extra_author": " Hamza Alkhatib"
            
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    },
            
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    {
            
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      "extra_author": " Claus Brenner"
            
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    },
            
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    {
            
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      "extra_author": " Steffen Sch\u00f6n"
            
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    }
            
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  ],
            
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  "groups": [],
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  "groups": [],
            
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  "have_copyright": "Yes",
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  "have_copyright": "Yes",
            
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  "id": "971783ee-fe56-4df3-9efc-1cd9e2d2e0fc",
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  "id": "971783ee-fe56-4df3-9efc-1cd9e2d2e0fc",
            
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  "isopen": false,
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  "isopen": false,
            
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  "license_id": "CC-BY-NC-3.0",
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  "license_id": "CC-BY-NC-3.0",
            
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  "license_title": "CC-BY-NC-3.0",
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  "license_title": "CC-BY-NC-3.0",
            
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  "maintainer": "Jeldrik Axmann",
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  "maintainer": "Jeldrik Axmann",
            
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  "maintainer_email": "jeldrik.axmann@ikg.uni-hannover.de",
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  "maintainer_email": "jeldrik.axmann@ikg.uni-hannover.de",
            
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  "metadata_created": "2023-02-22T08:31:17.861464",
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  "metadata_created": "2023-02-22T08:31:17.861464",
            
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  "metadata_modified": "2023-05-02T07:05:21.408004",
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  "metadata_modified": "2023-08-04T08:46:37.313840",
            
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  "name": 
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  "name": 
            
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ibniz-university-cooperative-perception-and-urban-navigation-dataset",
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ibniz-university-cooperative-perception-and-urban-navigation-dataset",
            
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  "notes": "##Abstract\r\nRecently published datasets have been 
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  "notes": "##A real-world multi-vehicle multi-modal V2V and V2X 
            
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dataset\r\n\r\nRecently published datasets have been 
            
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increasingly\r\ncomprehensive with respect to their variety of 
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increasingly\r\ncomprehensive with respect to their variety of 
            
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simultaneously\r\nused sensors, traffic scenarios, environmental 
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simultaneously\r\nused sensors, traffic scenarios, environmental 
            
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conditions, and\r\nprovided annotations. However, these datasets 
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conditions, and\r\nprovided annotations. However, these datasets 
            
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typically only\r\nconsider data collected by one independent vehicle. 
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typically only\r\nconsider data collected by one independent vehicle. 
            
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Hence, there\r\nis currently a lack of comprehensive, real-world, 
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Hence, there\r\nis currently a lack of comprehensive, real-world, 
            
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multi-vehicle\r\ndatasets fostering research on cooperative 
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multi-vehicle\r\ndatasets fostering research on cooperative 
            
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applications such as\r\nobject detection, urban navigation, or 
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applications such as\r\nobject detection, urban navigation, or 
            
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multi-agent SLAM. In\r\nthis paper, we aim to fill this gap by 
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multi-agent SLAM. In\r\nthis paper, we aim to fill this gap by 
            
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introducing the novel\r\nLUCOOP dataset, which provides 
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introducing the novel\r\nLUCOOP dataset, which provides 
            
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time-synchronized multi-modal\r\ndata collected by three interacting 
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time-synchronized multi-modal\r\ndata collected by three interacting 
            
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measurement vehicles. The\r\ndriving scenario corresponds to a 
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measurement vehicles. The\r\ndriving scenario corresponds to a 
            
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follow-up setup of multiple\r\nrounds in an inner city triangular 
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follow-up setup of multiple\r\nrounds in an inner city triangular 
            
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trajectory. Each vehicle was\r\nequipped with a broad sensor suite 
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trajectory. Each vehicle was\r\nequipped with a broad sensor suite 
            
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including at least one LiDAR\r\nsensor, one GNSS antenna, and up to 
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including at least one LiDAR\r\nsensor, one GNSS antenna, and up to 
            
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three IMUs. Additionally,\r\nUltra-Wide-Band (UWB) sensors were 
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three IMUs. Additionally,\r\nUltra-Wide-Band (UWB) sensors were 
            
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mounted on each vehicle,\r\nas well as statically placed along the 
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mounted on each vehicle,\r\nas well as statically placed along the 
            
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trajectory enabling both\r\nV2V and V2X range measurements. 
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trajectory enabling both\r\nV2V and V2X range measurements. 
            
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Furthermore, a part of the\r\ntrajectory was monitored by a total 
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Furthermore, a part of the\r\ntrajectory was monitored by a total 
            
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station resulting in a highly\r\naccurate reference trajectory. The 
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station resulting in a highly\r\naccurate reference trajectory. The 
            
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LUCOOP dataset also includes\r\na precise, dense 3D map point cloud, 
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LUCOOP dataset also includes\r\na precise, dense 3D map point cloud, 
            
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acquired simultaneously by\r\na mobile mapping system, as well as an 
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acquired simultaneously by\r\na mobile mapping system, as well as an 
            
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LOD2 city model of\r\nthe measurement area. We provide sensor 
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LOD2 city model of\r\nthe measurement area. We provide sensor 
            
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measurements in a\r\nmulti-vehicle setup for a trajectory of more than 
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measurements in a\r\nmulti-vehicle setup for a trajectory of more than 
            
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4 km and a\r\ntime interval of more than 26 minutes, respectively. 
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4 km and a\r\ntime interval of more than 26 minutes, respectively. 
            
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Overall, our\r\ndataset includes more than 54,000 LiDAR frames, 
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Overall, our\r\ndataset includes more than 54,000 LiDAR frames, 
            
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approximately\r\n700,000 IMU measurements, and more than 2.5 hours of 
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approximately\r\n700,000 IMU measurements, and more than 2.5 hours of 
            
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10 Hz\r\nGNSS raw measurements along with 1 Hz data from a 
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10 Hz\r\nGNSS raw measurements along with 1 Hz data from a 
            
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reference\r\nstation. Furthermore, we provide more than 6,000 total 
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reference\r\nstation. Furthermore, we provide more than 6,000 total 
            
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station\r\nmeasurements over a trajectory of more than 1 km and 
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station\r\nmeasurements over a trajectory of more than 1 km and 
            
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1,874\r\nV2V and 267 V2X UWB measurements. Additionally, we 
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1,874\r\nV2V and 267 V2X UWB measurements. Additionally, we 
            
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offer\r\n3D bounding box annotations for evaluating object 
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offer\r\n3D bounding box annotations for evaluating object 
            
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detection\r\napproaches, as well as highly accurate ground truth poses 
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detection\r\napproaches, as well as highly accurate ground truth poses 
            
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for\r\neach vehicle throughout the measurement campaign.\r\n\r\n## 
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for\r\neach vehicle throughout the measurement campaign.\r\n\r\n## 
            
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Data access\r\nThe data set is available at the following link: 
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Data access\r\n* The dataset is available 
            
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.de:8080/dataset/upload/users/icsens/axmann/LUCOOP/)\r\n\r\nAdditional 
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uni-hannover.de:8080/dataset/upload/users/icsens/axmann/LUCOOP/).\r\n* 
            
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information are provided and constantly updated in our README 
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Additional information are provided and constantly updated in our 
            
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document: 
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9-4452-87b9-2997da2b5a69/download/lucoop_readme_21_april_23.pdf).\r\n* 
            
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-699e57e55343/download/lucoop_readme.pdf)\r\n\r\n##Preview\r\n[![Watch 
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The corresponding paper is available 
            
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eexplore.ieee.org/document/10186693).\r\n\r\n\r\n##Preview\r\n[![Watch 
            
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the 
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the 
            
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f3b47-50ac-42e6-b4a0-8e1bb6a69e2f/download/teaser_video.mp4)\r\nSource 
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f3b47-50ac-42e6-b4a0-8e1bb6a69e2f/download/teaser_video.mp4)\r\nSource 
            
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LOD2 City model: Auszug aus den Geodaten des Landesamtes f\u00fcr 
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LOD2 City model: Auszug aus den Geodaten des Landesamtes f\u00fcr 
            
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Geoinformation und Landesvermessung Niedersachsen, \u00a92023, 
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Geoinformation und Landesvermessung Niedersachsen, \u00a92023, 
            
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n.de](https://www.lgln.niedersachsen.de/startseite/)\r\n<img>\r\n![Alt 
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n.de](https://www.lgln.niedersachsen.de/startseite/)\r\n<img>\r\n![Alt 
            
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text][id_lgln]\r\n[id_lgln]: 
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text][id_lgln]\r\n[id_lgln]: 
            
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e/resource/541747ed-3d6e-41c4-9046-15bba3702e3b/download/lgln_logo.png  
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e/resource/541747ed-3d6e-41c4-9046-15bba3702e3b/download/lgln_logo.png  
            
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\"LGLN logo\"\r\n</img>\r\n\r\n\r\n##Sensor Setup of the three 
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\"LGLN logo\"\r\n</img>\r\n\r\n\r\n##Sensor Setup of the three 
            
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measurement vehicles\r\n<img>\r\n![Alt text][id]\r\n[id]: 
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measurement vehicles\r\n<img>\r\n![Alt text][id]\r\n[id]: 
            
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49b0-40e6-b8d9-e49f420e3627/download/vans_with_redgreen_cs_vehicle.png  
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49b0-40e6-b8d9-e49f420e3627/download/vans_with_redgreen_cs_vehicle.png  
            
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\"Sensor Setup of the three measurement 
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\"Sensor Setup of the three measurement 
            
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vehicles\"\r\n<figcaption>Sensor setup of all the three vehicles: Each 
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vehicles\"\r\n<figcaption>Sensor setup of all the three vehicles: Each 
            
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vehicle is equipped with a LiDAR sensor (green), a UWB unit (orange), 
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vehicle is equipped with a LiDAR sensor (green), a UWB unit (orange), 
            
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a GNSS antenna (purple), and a Microstrain IMU (red). Additionally, 
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a GNSS antenna (purple), and a Microstrain IMU (red). Additionally, 
            
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each vehicle has its unique feature: Vehicle 1 has an additional LiDAR 
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each vehicle has its unique feature: Vehicle 1 has an additional LiDAR 
            
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at the trailer hitch (green) and a prism for the tracking of the total 
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at the trailer hitch (green) and a prism for the tracking of the total 
            
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station (dark red hexagon). Vehicle 2 provides an iMAR iPRENA (yellow) 
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station (dark red hexagon). Vehicle 2 provides an iMAR iPRENA (yellow) 
            
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and iMAR FSAS (blue) IMU, where the platform containing the IMUs is 
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and iMAR FSAS (blue) IMU, where the platform containing the IMUs is 
            
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mounted inside the car (dashed box). Vehicle 3 carries the RIEGL MMS 
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mounted inside the car (dashed box). Vehicle 3 carries the RIEGL MMS 
            
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(pink). Along with the sensors and platforms, the right-handed body 
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(pink). Along with the sensors and platforms, the right-handed body 
            
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frame of each vehicle is also 
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frame of each vehicle is also 
            
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indicated.</figcaption>\r\n</img>\r\n\r\n##3D map point 
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indicated.</figcaption>\r\n</img>\r\n\r\n##3D map point 
            
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cloud\r\n<img>\r\n![Alt text][idmap]\r\n[idmap]: 
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cloud\r\n<img>\r\n![Alt text][idmap]\r\n[idmap]: 
            
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urce/5b6b37cf-a991-4dc4-8828-ad12755203ca/download/map_point_cloud.png  
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urce/5b6b37cf-a991-4dc4-8828-ad12755203ca/download/map_point_cloud.png  
            
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\"3D map point cloud\"\r\n<figcaption>High resolution 3D map point 
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\"3D map point cloud\"\r\n<figcaption>High resolution 3D map point 
            
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cloud: Different locations and details along the trajectory. Colors 
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cloud: Different locations and details along the trajectory. Colors 
            
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according to reflectance 
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according to reflectance 
            
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values.</figcaption>\r\n</img>\r\n\r\n##Measurement 
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values.</figcaption>\r\n</img>\r\n\r\n##Measurement 
            
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scenario\r\n<img>\r\n![Alt text][id1]\r\n[id1]: 
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scenario\r\n<img>\r\n![Alt text][id1]\r\n[id1]: 
            
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7-8544-4788-bccf-7a28ccfa702a/download/scenario_with_osm_reference.png  
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7-8544-4788-bccf-7a28ccfa702a/download/scenario_with_osm_reference.png  
            
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\"Measurement scenario\"\r\n<figcaption>Driven trajectory and 
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\"Measurement scenario\"\r\n<figcaption>Driven trajectory and 
            
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locations of the static sensors: The blue hexagons indicate the 
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locations of the static sensors: The blue hexagons indicate the 
            
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positions of the static UWB\r\nsensors, the orange star represents the 
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positions of the static UWB\r\nsensors, the orange star represents the 
            
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location of the total station, and the orange shaded area illustrates 
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location of the total station, and the orange shaded area illustrates 
            
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the coverage of\r\nthe total station. The route of the three 
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the coverage of\r\nthe total station. The route of the three 
            
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measurement vehicles is shown in purple. Background map: 
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measurement vehicles is shown in purple. Background map: 
            
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[OpenStreetMap 
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[OpenStreetMap 
            
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/www.openstreetmap.org/copyright)</figcaption>\r\n</img>\r\n\r\n##Data 
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ww.openstreetmap.org/copyright)</figcaption>\r\n</img>\r\n\r\n[![Watch 
            
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the 
            
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7b17-1d43-4464-b4f7-35d631ca041d/download/topview_rate5.mp4)\r\nSource 
            
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LOD2 City model: Auszug aus den Geodaten des Landesamtes f\u00fcr 
            
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Geoinformation und Landesvermessung Niedersachsen, \u00a92023, 
            
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de](https://www.lgln.niedersachsen.de/startseite/)\r\n\r\n\r\n##Number 
            
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of annotations per class (regularly updated)\r\n\r\n<img>\r\n![Alt 
            
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text][id_ann]\r\n[id_ann]: 
            
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resource/954fb0b3-04a3-4d29-89c3-80c6b8b91c4f/download/annotations.png  
            
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\"Number of annotations per class\"\r\n</img>\r\n\r\n[![Watch the 
            
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55-fb84-4534-835a-b535305492f5/download/perspectiveview.mp4)\r\nSource 
            
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LOD2 City model: Auszug aus den Geodaten des Landesamtes f\u00fcr 
            
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Geoinformation und Landesvermessung Niedersachsen, \u00a92023, 
            
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tps://www.lgln.niedersachsen.de/startseite/)\r\n\r\n\r\n\r\n\r\n##Data 
            
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structure\r\n<img>\r\n![Alt text][id_d]\r\n[id_d]: 
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structure\r\n<img>\r\n![Alt text][id_d]\r\n[id_d]: 
            
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ource/7358ed31-9886-4c74-bec2-6868d577a880/download/data_structure.png  
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ource/7358ed31-9886-4c74-bec2-6868d577a880/download/data_structure.png  
            
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\"Data structure\"\r\n</img>\r\n\r\n##Data format\r\n<img>\r\n![Alt 
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\"Data structure\"\r\n</img>\r\n\r\n##Data format\r\n<img>\r\n![Alt 
            
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text][id_f]\r\n[id_f]: 
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text][id_f]\r\n[id_f]: 
            
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resource/fc795ec2-f920-4415-aac6-6ad3be3df0a9/download/data_format.png  
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resource/fc795ec2-f920-4415-aac6-6ad3be3df0a9/download/data_format.png  
            
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\"Data format\"\r\n</img>\r\n\r\n##Gallery\r\n<!--\r\n<img>\r\n![Alt 
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\"Data format\"\r\n</img>\r\n\r\n##Gallery\r\n<!--\r\n<img>\r\n![Alt 
            
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text][id2]\r\n[id2]: 
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text][id2]\r\n[id2]: 
            
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a1e3fe/resource/5edca245-3c0f-4757-bdf5-ef37084d6d80/download/van1.png  
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a1e3fe/resource/5edca245-3c0f-4757-bdf5-ef37084d6d80/download/van1.png  
            
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\"Van 1\"\r\n<figcaption>Van 
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\"Van 1\"\r\n<figcaption>Van 
            
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1</figcaption>\r\n</img>\r\n\r\n<img>\r\n![Alt text][id3]\r\n[id3]: 
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1</figcaption>\r\n</img>\r\n\r\n<img>\r\n![Alt text][id3]\r\n[id3]: 
            
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1e3fe/resource/a9cd7ff0-2184-4990-8091-6519016b10be/download/van2.jpeg  
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\"Van 2\"\r\n<figcaption>Van 
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\"Van 2\"\r\n<figcaption>Van 
            
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2</figcaption>\r\n</img>\r\n\r\n<img>\r\n![Alt text][id4]\r\n[id4]: 
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2</figcaption>\r\n</img>\r\n\r\n<img>\r\n![Alt text][id4]\r\n[id4]: 
            
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a1e3fe/resource/98d69436-0e14-47fb-bf2d-72f970348e69/download/van3.jpg  
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a1e3fe/resource/98d69436-0e14-47fb-bf2d-72f970348e69/download/van3.jpg  
            
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\"Van 3\"\r\n<figcaption>Van 
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\"Van 3\"\r\n<figcaption>Van 
            
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3</figcaption>\r\n</img>\r\n-->\r\n\r\n<img>\r\n![Alt 
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3</figcaption>\r\n</img>\r\n-->\r\n\r\n<img>\r\n![Alt 
            
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text][id6]\r\n[id6]: 
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text][id6]\r\n[id6]: 
            
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resource/a1974957-5ce2-456c-9f44-9d05c5a14b16/download/vans_merged.png  
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resource/a1974957-5ce2-456c-9f44-9d05c5a14b16/download/vans_merged.png  
            
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\"Measurement vehicles\"\r\n<figcaption>From left to right: Van 1, van 
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\"Measurement vehicles\"\r\n<figcaption>From left to right: Van 1, van 
            
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2, van 3.</figcaption>\r\n</img>\r\n\r\n<img>\r\n![Alt 
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2, van 3.</figcaption>\r\n</img>\r\n\r\n<img>\r\n![Alt 
            
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text][id5]\r\n[id5]: 
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text][id5]\r\n[id5]: 
            
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/resource/53a58500-8847-4b3c-acd4-a3ac27fc8575/download/ts_uwb_mms.png  
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/resource/53a58500-8847-4b3c-acd4-a3ac27fc8575/download/ts_uwb_mms.png  
            
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\"\"\r\n<figcaption>From left to right: Tracking of the prism on van 1 
165
\"\"\r\n<figcaption>From left to right: Tracking of the prism on van 1 
            
124
by means of the MS60\r\ntotal station,  the detected prism from the 
166
by means of the MS60\r\ntotal station,  the detected prism from the 
            
125
view point of the MS60 total station, PulsON 440 Ultra Wide Band (UWB) 
167
view point of the MS60 total station, PulsON 440 Ultra Wide Band (UWB) 
            
126
sensors, RIEGL VMX-250 Mobile Mapping 
168
sensors, RIEGL VMX-250 Mobile Mapping 
            
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System.</figcaption>\r\n</img>\r\n\r\n## Acknowledgement\r\nThis 
169
System.</figcaption>\r\n</img>\r\n\r\n## Acknowledgement\r\nThis 
            
128
measurement campaign could not have been carried\r\nout without the 
170
measurement campaign could not have been carried\r\nout without the 
            
129
help of many contributors. At this point, we\r\nthank Yuehan Jiang 
171
help of many contributors. At this point, we\r\nthank Yuehan Jiang 
            
130
(Institute for Autonomous Cyber-Physical\r\nSystems, Hamburg), 
172
(Institute for Autonomous Cyber-Physical\r\nSystems, Hamburg), 
            
131
Franziska Altemeier, Ingo Neumann,\r\nS\u00f6ren Vogel, Frederic Hake 
173
Franziska Altemeier, Ingo Neumann,\r\nS\u00f6ren Vogel, Frederic Hake 
            
132
(all Geodetic Institute, Hannover),\r\nColin Fischer (Institute of 
174
(all Geodetic Institute, Hannover),\r\nColin Fischer (Institute of 
            
133
Cartography and Geoinformatics,\r\nHannover), Thomas Maschke, Tobias 
175
Cartography and Geoinformatics,\r\nHannover), Thomas Maschke, Tobias 
            
134
Kersten, Nina Fletling\r\n(all Institut f\u00fcr Erdmessung, 
176
Kersten, Nina Fletling\r\n(all Institut f\u00fcr Erdmessung, 
            
135
Hannover), J\u00f6rg Blankenbach\r\n(Geodetic Institute, Aachen), 
177
Hannover), J\u00f6rg Blankenbach\r\n(Geodetic Institute, Aachen), 
            
136
Florian Alpen (Hydromapper\r\nGmbH), Allison Kealy (Victorian 
178
Florian Alpen (Hydromapper\r\nGmbH), Allison Kealy (Victorian 
            
137
Department of Environment,\r\nLand, Water and Planning, Melbourne), 
179
Department of Environment,\r\nLand, Water and Planning, Melbourne), 
            
138
G\u00fcnther Retscher,\r\nJelena Gabela (both Department of Geodesy 
180
G\u00fcnther Retscher,\r\nJelena Gabela (both Department of Geodesy 
            
139
and Geoin-\r\nformation, Wien), Wenchao Li (Solinnov Pty Ltd), 
181
and Geoin-\r\nformation, Wien), Wenchao Li (Solinnov Pty Ltd), 
            
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Adrian\r\nBingham (Applied Artificial Intelligence Institute, 
182
Adrian\r\nBingham (Applied Artificial Intelligence Institute, 
            
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Burwood),\r\nand the student assistants Manuel Kramer, Khaled 
183
Burwood),\r\nand the student assistants Manuel Kramer, Khaled 
            
142
Ahmed,\r\nLeonard G\u00f6ttert, Dennis Mu\u00dfgnug, Chengqi Zhou, and 
184
Ahmed,\r\nLeonard G\u00f6ttert, Dennis Mu\u00dfgnug, Chengqi Zhou, and 
            
143
We-\r\nicheng Zhang. Thanks to the Landesamt f\u00fcr 
185
We-\r\nicheng Zhang. Thanks to the Landesamt f\u00fcr 
            
144
Geoinformation\r\nand Landesermessung Niedersachsen (LGLN)/Zentrale 
186
Geoinformation\r\nand Landesermessung Niedersachsen (LGLN)/Zentrale 
            
145
Stelle\r\nSAPOS\u00ae for providing the virtual reference station 
187
Stelle\r\nSAPOS\u00ae for providing the virtual reference station 
            
146
data, in-\r\nfrastructure and reliable high quality. This project is 
188
data, in-\r\nfrastructure and reliable high quality. This project is 
            
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supported\r\nby the German Research Foundation (DFG), as part of 
189
supported\r\nby the German Research Foundation (DFG), as part of 
            
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the\r\nResearch Training Group i.c.sens, GRK 2159, \u201dIntegrity 
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the\r\nResearch Training Group i.c.sens, GRK 2159, \u201dIntegrity 
            
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and\r\nCollaboration in Dynamic Sensor Networks\u201d.",
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and\r\nCollaboration in Dynamic Sensor Networks\u201d.",
            
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Urban Navigation Dataset",
            
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