@inproceedings{Perzylo2015d, author = {Perzylo, Alexander and Griffiths, Sascha and Lafrenz, Reinhard and Knoll, Alois}, title = {Generating Grammars for Natural Language Understanding from Knowledge about Actions and Objects}, booktitle = {Proceedings of the IEEE International Conference on Robotics and Biomimetics (ROBIO)}, pages = {2008--2013}, year = {2015}, address = {Zhuhai, China}, abstract = {Many applications in the fields of Service Robotics and Industrial Human-Robot Collaboration, require interaction with a human in a potentially unstructured environment. In many cases, a natural language interface can be helpful, but it requires powerful means of knowledge representation and processing, e.g., using ontologies and reasoning. In this paper we present a framework for the automatic generation of natural language grammars from ontological descriptions of robot tasks and interaction objects, and their use in a natural language interface. Robots can use it locally or even share this interface component through the RoboEarth framework in order to benefit from features such as referent grounding, ambiguity resolution, task identification, and task assignment.}, doi = {10.1109/ROBIO.2015.7419068}, keywords = {robotics, smerobotics}, url = {http://youtu.be/mgPQevfTWP8}, } @inproceedings{Tenorth2013b, author = {Tenorth, Moritz and Perzylo, Alexander and Lafrenz, Reinhard and Beetz, Michael}, title = {{The RoboEarth language: Representing and Exchanging Knowledge about Actions, Objects and Environments (Extended Abstract)}}, booktitle = {IJCAI'13: Proceedings of the 23rd international joint conference on Artifical intelligence}, pages = {3091--3095}, year = {2013}, month = aug, address = {Beijing, China}, note = {Best papers and thesis in sister conferences track. (Invited Paper)}, abstract = {The community-based generation of content has been tremendously successful in the World Wide Web - people help each other by providing information that could be useful to others. We are trying to transfer this approach to robotics in order to help robots acquire the vast amounts of knowledge needed to competently perform everyday tasks. RoboEarth is intended to be a web community by robots for robots to autonomously share descriptions of tasks they have learned, object models they have created, and environments they have explored. In this paper, we report on the formal language we developed for encoding this information and present our approaches to solve the inference problems related to finding information, to determining if information is usable by a robot, and to grounding it on the robot platform.}, keywords = {robotics}, } @article{Tenorth2013a, author = {Tenorth, Moritz and Perzylo, Alexander and Lafrenz, Reinhard and Beetz, Michael}, title = {{Representation and Exchange of Knowledge about Actions, Objects, and Environments in the RoboEarth Framework}}, journal = {IEEE Transactions on Automation Science and Engineering (T-ASE)}, volume = {10}, number = {3}, pages = {643-651}, year = {2013}, note = {(Best Paper Award Finalist)}, abstract = {The community-based generation of content has been tremendously successful in the World Wide Web - people help each other by providing information that could be useful to others. We are trying to transfer this approach to robotics in order to help robots acquire the vast amounts of knowledge needed to competently perform everyday tasks. RoboEarth is intended to be a web community by robots for robots to autonomously share descriptions of tasks they have learned, object models they have created, and environments they have explored. In this paper, we report on the formal language we developed for encoding this information and present our approaches to solve the inference problems related to finding information, to determining if information is usable by a robot, and to grounding it on the robot platform. Note to practitioners: In this paper, we report on a formal language for knowledge representation that is used in the ROBOEARTH system, a web-based knowledge base intended to be like a "Wikipedia for robots." The objective is to enable robots to share information about how to perform actions, how to recognize and interact with objects, and where to find objects in an environment. The developed language allows to store such information in a format that supports logical inference, so that robots can for example autonomously decide if they have all prerequisites needed for performing a described action. In laboratory experiments, the system has been applied to the exchange of pick-and-place style activities between two mobile manipulation robots. We are currently extending the representation towards more fine-grained action specifications.}, doi = {10.1109/tase.2013.2244883}, keywords = {robotics}, }