Merge pull request #390 from agri-gaia/doc/updatePublications

Doc/update publications

README.md

@@ -33,14 +33,14 @@
 
 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-TemporalSemantic Environment Representation for Autonomous Mobile Robots_.
+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 changes over time, as for example agricultural environments, can be understood based on
+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.
 
 ## Quick Start
@@ -85,37 +85,38 @@ volumes:
 
 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 are given and basic tutorials are given.
+instructions and basic tutorials are given.
 
 The [Doxygen](https://doxygen.nl/) based code documentation can be found [here](https://agri-gaia.github.io/seerep/doxygen).
 
 ## Related Publications
 
 ```bibtex
-@inproceedings{hoellmann2021seerep,
-  author = {Höllmann, Mark and Hertzberg, Joachim},
-  title = {SEEREP: towards a spatio-temporal-SEmantic Environment REPresentation for robots in an agricultural context},
-  booktitle = {Perception and Navigation for Autonomous Robotics in Unstructured and Dynamic Environments Workshop on
-  2021 IEEE/RSJ International Conference on Intelligent Robots and Systems},
-  year = {2021},
-  month = {10}
-}
-
-@inproceedings{niemeyer2022seerep,
-  author = {Niemeyer, Mark and Pütz, Sebastian and Hertzberg, Joachim},
-  title = {A Spatio-Temporal-Semantic Environment Representation for Autonomous Mobile Robots equipped with
-  various Sensor Systems},
-  booktitle = {2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems},
-  year = {2022},
-  month = {9},
+@inproceedings{Niemeyer2024,
+  author = {Niemeyer, Mark and Arkenau, Julian and Pütz, Sebastian and Hertzberg, Joachim},
+  title = {Streamlined Acquisition of Large Sensor Data for Autonomous Mobile Robots to
+  Enable Efficient Creation and Analysis of Datasets },
+  booktitle = {2024 IEEE International Conference on Robotics and Automation (ICRA)},
+  year = {2024},
   publisher = {IEEE}
 }
 
-@inproceedings{Niemeyer2023Anchoring,
+@inproceedings{Niemeyer2023,
   author = {Niemeyer, Mark and Renz, Marian and Hertzberg, Joachim},
-  title = {Object Anchoring for Autonomous Robots using the Spatio-Temporal-Semantic Environment Representation SEEREP},
-  booktitle = {KI 2023. German Conference on Artificial Intelligence (KI-2023), 46th, September 27-29, Berlin, Germany},
+  title = {Object Anchoring for Autonomous Robots using the Spatio-Temporal-Semantic
+  Environment Representation SEEREP},
+  booktitle = {KI 2023. German Conference on Artificial Intelligence (KI-2023)},
   year = {2023},
   publisher = {Springer}
 }
+
+@inproceedings{Niemeyer2022,
+  author = {Niemeyer, Mark and Pütz, Sebastian and Hertzberg, Joachim},
+  title = {A Spatio-Temporal-Semantic Environment Representation for Autonomous Mobile Robots
+  equipped with   various Sensor Systems},
+  booktitle = {2022 IEEE International Conference on Multisensor Fusion and Integration for
+  Intelligent Systems (MFI)},
+  year = {2022},
+  publisher = {IEEE}
+}
 ```