2014 |
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Dietrich, André; Zug, Sebastian; Mohammad, Siba; Kaiser, Jörg Distributed Management and Representation of Data and Context in Robotic Applications (Inproceeding) Proceedings of the IEEE/RSI International Conference on Intelligent Robobts and Systems (IROS), Chicago, Illinois, 2014, (accepted). (Abstract | Links | BibTeX | Tags: Environement Representation, Robotics, Smart Environment) @inproceedings{dietrich2014iros,
title = {Distributed Management and Representation of Data and Context in Robotic Applications}, author = {André Dietrich and Sebastian Zug and Siba Mohammad and Jörg Kaiser}, url = {http://eos.cs.ovgu.de/wp-content/uploads/2015/06/Distributed-Management-and-Representation-of-Data-and-Context-in-Robotic-Applications.pdf http://eos.cs.ovgu.de/wp-content/uploads/2015/06/ImpressJS-Slides.zip}, year = {2014}, date = {2014-09-14}, booktitle = {Proceedings of the IEEE/RSI International Conference on Intelligent Robobts and Systems (IROS)}, address = {Chicago, Illinois}, abstract = {The traditional, isolated data handling in sensor-actuator systems does not fulfill the requirements of robots that need to interact with their smart environment. Consequently, we have to develop new mechanisms for adaptive data and context handling. We firstly investigate what types of data are present within smart environments and how they can be classified and organized. Only if the available data can be structured, it can be queried and thus put into context. This is because the variety of data and possible interpretations is tremendous, ranging from measurement values, sensor and robot descriptions/states/commands, to environmental data, such as positions, maps, spatial relations, etc. To cope with this diversity, we developed a solution capable of storing and accessing data within a distributed environment by providing additional context information. Furthermore, we describe how this information can be assembled in a task-oriented manner. This enables robots to dynamically generate environmental abstractions by using data from different sources and also enables them to incorporate external sensor measurements.}, The traditional, isolated data handling in sensor-actuator systems does not fulfill the requirements of robots that need to interact with their smart environment. Consequently, we have to develop new mechanisms for adaptive data and context handling.
We firstly investigate what types of data are present within smart environments and how they can be classified and organized. Only if the available data can be structured, it can be queried and thus put into context. This is because the variety of data and possible interpretations is tremendous, ranging from measurement values, sensor and robot descriptions/states/commands, to environmental data, such as positions, maps, spatial relations, etc. To cope with this diversity, we developed a solution capable of storing and accessing data within a distributed environment by providing additional context information. Furthermore, we describe how this information can be assembled in a task-oriented manner. This enables robots to dynamically generate environmental abstractions by using data from different sources and also enables them to incorporate external sensor measurements. |
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Dietrich, André; Mohammad, Siba; Zug, Sebastian; Kaiser, Jörg ROS Meets Cassandra: Data Management in Smart Environments with NoSQL (Conference) Proc. of the 11th International Baltic Conference (Baltic DB&IS 2014), Tallinn, Estonia, 2014. (Abstract | Links | BibTeX | Tags: Cassandra, Database, Robotics, Smart Environment) @conference{dietrich2014cassandra,
title = {ROS Meets Cassandra: Data Management in Smart Environments with NoSQL}, author = {André Dietrich and Siba Mohammad and Sebastian Zug and Jörg Kaiser}, url = {http://eos.cs.ovgu.de/wp-content/uploads/2014/09/ROS-Meets-Cassandra-Data-Management-in-Smart-Environments-with-NoSQL.pdf http://eos.cs.ovgu.de/wp-content/uploads/2015/06/sozi-presentation.svg}, year = {2014}, date = {2014-06-08}, booktitle = {Proc. of the 11th International Baltic Conference (Baltic DB&IS 2014)}, pages = {43–54}, address = {Tallinn, Estonia}, abstract = {Distributed and smart environments can be seen as a distributed storage for data, information, and knowledge. Thus, one of the key challenges for future smart environments is the organization, access, and querying of this distributed storage while allowing entities to dynamically access both real-time and historical data. A relatively new approach for data management, the NoSQL databases, promises data-model flexibility, high scalability, and availability without the overhead in the fully fledged traditional Relational Database Management Systems (RDBMS)s. In our work, we exploit the previous benefits of NoSQL databases by integrating Cassandra into the Robotic Operating System (ROS). We evaluated our approach in two scenarios; within a realistic robotic exploration and with a pessimistic benchmark using randomly generated data.}, keywords = {Cassandra, Database, Robotics, Smart Environment} } Distributed and smart environments can be seen as a distributed storage for data, information, and knowledge. Thus, one of the key challenges for future smart environments is the organization, access, and querying of this distributed storage while allowing entities to dynamically access both real-time and historical data. A relatively new approach for data management, the NoSQL databases, promises data-model flexibility, high scalability, and availability without the overhead in the fully fledged traditional Relational Database Management Systems (RDBMS)s. In our work, we exploit the previous benefits of NoSQL databases by integrating Cassandra into the Robotic Operating System (ROS). We evaluated our approach in two scenarios; within a realistic robotic exploration and with a pessimistic benchmark using randomly generated data.
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