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| # SEEREP | ||
| # | ||
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|  | ||
| <div align="center"> | ||
| <img alt="Redoc logo" src="docs/logo/Seerep_Logo.svg" width="300px" /> | ||
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|  | ||
| [](./LICENSE) | ||
| [](https://github.com/agri-gaia/seerep/actions) | ||
| [](./.pre-commit-config.yaml) | ||
| [](./docker) | ||
| [](https://pypi.org/project/seerep-grpc/) | ||
| <!--  --> | ||
| <h3> Spatio-Temporal-Semantic Sensor Data Management <br> | ||
| for Agricultural Robotics </h3> | ||
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| ## Table of Contents | ||
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| - [Maintainer](#maintainer) | ||
| - [General](#general) | ||
| - [Quick Start](#quick-start) | ||
| - [Documentation](#documentation) | ||
| - [Related Publications](#related-publications) | ||
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| <!-- - [Related Publications](#related-publications) --> | ||
| [](https://github.com/agri-gaia/seerep/actions) | ||
|  | ||
| [](./LICENSE) | ||
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| ## Maintainer | ||
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| [Mark Niemeyer](https://github.com/Mark-Niemeyer)<br> | ||
| [[email protected]](mailto:[email protected]) | ||
| <b><a href="https://agri-gaia.github.io/seerep/mkdocs/home/index.html"> | ||
| Documentation</a></b> | ||
| | | ||
| <b><a href="https://github.com/agri-gaia/seerep/tree/main/examples/python/gRPC"> | ||
| Examples</a></b> | ||
| </div> | ||
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| [German Research Center for Artificial Intelligence](https://www.dfki.de/en/web)<br> | ||
| [DFKI Niedersachsen](https://www.dfki.de/en/web/about-us/locations-contact/osnabrueck-oldenburg)<br> | ||
| [Plan-Based Robot Control](https://www.dfki.de/en/web/research/research-departments/plan-based-robot-control)<br> | ||
| ## Table of Contents | ||
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| ## General | ||
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| The large amount of temporally and spatially high resolution sensor data of | ||
| autonomous mobile robots that have to be collected in today’s systems require a | ||
| structured and, above all, efficient management and storage already during the | ||
| robot mission. We present SEEREP: A _Spatio-Temporal-Semantic Environment | ||
| Representation for Autonomous Mobile Robots_. SEEREP deals with spatial, | ||
| temporal and semantic linked data at once and provides an efficient query | ||
| interface for all three modalities that can be combined for high-level analyses. | ||
| It supports the most popular robotic sensor data such as images and point clouds, | ||
| as well as sensor and robot coordinate frames changing over time. Furthermore, | ||
| SEEREP provides an efficient HDF5-based storage system running on the robot | ||
| during operation compatible with ROS and the corresponding sensor message | ||
| definitions. The compressed HDF5 data backend can be transferred efficiently to | ||
| an application server with a running SEEREP query server providing gRPC interfaces | ||
| with Protobuf and Flattbuffer message types. Partially unstructured environments | ||
| that change over time, as for example agricultural environments, can be understood | ||
| based on high-level planning and reasoning systems using the SEEREP query server. | ||
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| ## Quick Start | ||
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| To deploy the server locally the following `docker run` command or the following | ||
| `docker-compose.yml` can be used. | ||
| - [Features](#-features) | ||
| - [Motivation](#muscle-motivation) | ||
| - [Getting Started](#-getting-started) | ||
| - [Maintainer](#wrench-maintainer) | ||
| - [Related Publications](#memo-related-publications) | ||
| - [License](#-license) | ||
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| ## 🎯 Features | ||
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| - Robotic sensor data management integrated with [ROS](https://www.ros.org/). | ||
| - Creation of sub-datasets based on sub-symbolic information (positions, | ||
| timestamps) and their corresponding symbolic (semantic) information. | ||
| - Automated generation and evaluation (e.g neural network predictions) of | ||
| datasets. | ||
| - GDPR filtering of datasets (e.g excluding public roads) based on spatial | ||
| polygon queries. | ||
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| ## :muscle: Motivation | ||
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| A key transition in robotics involves the adoption of data-driven approaches. | ||
| As a result, increasing amounts of data are being captured by high-resolution | ||
| sensors such as cameras and LiDAR. | ||
| With ROS, the typical workflow involves recording rosbags during missions and | ||
| uploading the resulting files to network or blob storage, organized according to | ||
| use-case specific hierarchies. | ||
| Later retrieval of data with specific properties, such as particular weather | ||
| conditions or a specific area of interest, is non-trivial. The relevant data | ||
| must be downloaded to open the rosbag where access to the data is only provided | ||
| through the time modality. | ||
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| In contrast, SEEREP offers an integrated solution for managing robotic sensor | ||
| data and generating sub-datasets based on spatial, temporal, or semantic | ||
| queries. Simplifying the workflow to uploading the sensor data post-mission and | ||
| offering a gRPC-based query interface for subsequent applications. | ||
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| ## 🚀 Getting Started | ||
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| The simplest way to start SEEREP is by using `docker compose` with the | ||
| configuration provided in the `docker/server` directory: | ||
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| ```bash | ||
| docker run \ | ||
| --volume=seerep-data:/mnt/seerep-data \ | ||
| --publish=9090:9090 \ | ||
| --name=seerep_server \ | ||
| --tty \ | ||
| ghcr.io/agri-gaia/seerep_server:latest \ | ||
| --data-folder=/mnt/seerep-data | ||
| git clone https://github.com/agri-gaia/seerep.git | ||
| cd seerep/docker/server | ||
| docker compose up | ||
| ``` | ||
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| Example docker-compose.yml: | ||
| Which should produce an output like this: | ||
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| ```bash | ||
| version: "3.9" | ||
| services: | ||
| seerep: | ||
| image: ghcr.io/agri-gaia/seerep_server:latest | ||
| tty: true | ||
| container_name: seerep_server | ||
| ports: | ||
| # the gRPC port | ||
| - 9090:9090 | ||
| volumes: | ||
| # persist the data folder | ||
| - seerep-data:/mnt/seerep-data | ||
| environment: | ||
| - TZ=Europe/Berlin | ||
| - SEEREP_DATA_FOLDER=/mnt/seerep-data | ||
| - SEEREP_LOG_PATH=/mnt/seerep-data/log | ||
| - SEEREP_LOG_LEVEL=info | ||
| volumes: | ||
| seerep-data: | ||
| seerep_server | [2024-07-11 13:40:00.853800]<info>: Initialized logging | ||
| seerep_server | [2024-07-11 13:40:00.860308]<info>: The used logging folder is: /mnt/seerep_data/log/ | ||
| seerep_server | [2024-07-11 13:40:00.860730]<info>: Current timezone: CET | ||
| seerep_server | [2024-07-11 13:40:00.861233]<info>: SEEREP version: N/A | ||
| seerep_server | [2024-07-11 13:40:00.861567]<info>: The used data folder is: /mnt/seerep_data/ | ||
| seerep_server | [2024-07-11 13:40:00.865541]<info>: Addded Protocol Buffers gRPC-services | ||
| seerep_server | [2024-07-11 13:40:00.867241]<info>: Added Flatbuffers gRPC services | ||
| seerep_server | [2024-07-11 13:40:00.903333]<info>: Serving gRPC Server on "[::]:9090" | ||
| ``` | ||
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| ## Documentation | ||
| For other ways to deploy SEEREP, check the | ||
| [documentation](https://agri-gaia.github.io/seerep/mkdocs/getting-started/server_deployment/). | ||
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| The general [MkDocs](https://www.mkdocs.org/) based documentation of this project | ||
| is available [here](https://agri-gaia.github.io/seerep/mkdocs/home/). There the | ||
| general architecture is described, installation instructions and basic tutorials | ||
| are given. | ||
| Refer to the [examples section](https://github.com/agri-gaia/seerep/tree/update-readme/examples/python/gRPC) | ||
| for instructions on uploading data. | ||
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| The [Doxygen](https://doxygen.nl/) based code documentation can be found | ||
| [here](https://agri-gaia.github.io/seerep/doxygen). | ||
| ## :wrench: Maintainer | ||
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| ## Related Publications | ||
| [Mark Niemeyer](https://github.com/Mark-Niemeyer) <br> | ||
| [[email protected]](mailto:[email protected]) | ||
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| [German Research Center for Artificial Intelligence](https://www.dfki.de/en/web)<br> | ||
| [DFKI Niedersachsen](https://www.dfki.de/en/web/about-us/locations-contact/osnabrueck-oldenburg)<br> | ||
| [Plan-Based Robot Control](https://www.dfki.de/en/web/research/research-departments/plan-based-robot-control)<br> | ||
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| ## :memo: Related Publications | ||
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| ```bibtex | ||
| @inproceedings{Niemeyer2024, | ||
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@@ -129,3 +125,7 @@ The [Doxygen](https://doxygen.nl/) based code documentation can be found | |
| publisher = {IEEE} | ||
| } | ||
| ``` | ||
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| ## 📄 License | ||
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| This project is open-sourced software licensed under the [BSD 3-Clause license](./LICENSE). | ||
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