Abstract
Autonomous robots are playing important roles in academic, technological, and scientific activities. Thus, their behavior is getting more complex, particularly, in tasks related to mapping an environment and localizing themselves. These tasks comprise the Simultaneous Localization and Mapping (SLAM) problem. Representation of knowledge related to the SLAM problem with a standard, flexible, and well-defined model, provides the base to develop efficient and interoperable solutions. As many existing works demonstrate, Semantic Web seems to be a clear approach, since they have formulated ontologies, as the base data model to represent such knowledge. In this article, we survey the most popular and recent SLAM ontologies with our aim being threefold: (i) propose a classification of SLAM ontologies according to the main knowledge needed to model the SLAM problem; (ii) identify existing ontologies for classifying, comparing, and contrasting them, in order to conceptualize SLAM domain for mobile robots; and (iii) pin-down lessons to learn from existing solutions in order to design better solutions and identify new research directions and further improvements. We compare the identified SLAM ontologies according to the proposed classification and, finally, we explore new data fields to enrich existing ontologies and highlight new possibilities in terms of performance and efficiency for SLAM solutions.
- Julita Bermejo Alonso, Ricardo Sanz Bravo, Manuel Rodríguez, and Carlos Hernández Corbato. 2011. Engineering an ontology for autonomous systems - The OASys ontology. In Proceedings of the International Conference on Knowledge Engineering and Ontology Development, KEOD. Springer Verlag, Berlin, Alemania, 47--58.Google Scholar
- Grigoris Antoniou and Frank van Harmelen. 2004. Web Ontology Language: OWL. In: Handbook on Ontologies. Berlin, Heidelberg. Springer.Google Scholar
- T. Bailey and H. Durrant-Whyte. 2006. Simultaneous localization and mapping (SLAM): Part II. Proceedings of the IEEE Robotics Automation Magazine 13, 3 (Sep. 2006), 108--117.Google ScholarCross Ref
- Lamia Belouaer, Maroua Bouzid, and Abdel-Illah Mouaddib. 2010. Ontology based spatial planning for human-robot interaction. In Proceeding of the 17th International Symposium on Temporal Representation and Reasoning, Vol. 1. 103--110.Google ScholarDigital Library
- Tim Berners-Lee, James Hendler, and Ora Lassila. 2001. The semantic web. Scientific American 284, 5 (2001), 34--43.Google ScholarCross Ref
- T. Berners-Lee, L. Masinter, and M. McCahill. 1994. RFC1738: Uniform Resource Locators (URL). https://dl.acm.org/doi/book/10.17487/RFC1738.Google Scholar
- Tim Bray, Jean Paoli, Michael Sperberg-McQueen, Eve Maler, and Franois Yergeau. 2000. Extensible markup language (XML) 1.0.Google Scholar
- Stefan Brunner, Markus Kucera, and Thomas Waas. 2017. Ontologies used in robotics: A survey with an outlook for automated driving. In Proceedings of the IEEE International Conference on Vehicular Electronics and Safety (ICVES). 81--84.Google ScholarCross Ref
- Guy Burroughes and Yang Gao. 2016. Ontology-based self-reconfiguring guidance, navigation, and control for planetary rovers. Journal of Aerospace Information Systems 13 (2016), 316--328.Google ScholarCross Ref
- Joel Carbonera, Sandro Fiorini, Edson Prestes, Vitor Jorge, Mara Abel, Raj Madhavan, Angela Locoro, Paulo Gonçalves, Tamas Haidegger, and Craig Schlenoff. 2013. Defining positionig in a core ontology for robotics. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems. 1867--1872.Google Scholar
- Michael Cashmore, Maria Fox, Derek Long, Daniele Magazzeni, Bram Ridder, Arnau Carrera, N. Palomeras, N. Hurtós, and Marc Carreras. 2015. Rosplan: Planning in the robot operating system. In Proceedings of the International Conference on Automated Planning and Scheduling, ICAPS. 333--341.Google Scholar
- Doo Soo Chang, Gun Hee Cho, and Yong Suk Choi. 2020. Ontology-based knowledge model for human-robot interactive services. In Proceedings of the 35th Annual ACM Symposium on Applied Computing. 2029--2038.Google Scholar
- Mark Coeckelbergh, Cristina Pop, Ramona Simut, Andreea Peca, Sebastian Pintea, Daniel David, and Bram Vanderborght. 2016. A survey of expectations about the role of robots in robot-assisted therapy for children with ASD: Ethical acceptability, trust, sociability, appearance, and attachment. Science and Engineering Ethics 22, 1 (2016), 47--65.Google ScholarCross Ref
- Jonathan Crespo, R. Barber, and O. M. Mozos. 2017. Relational model for robotic semantic navigation in indoor environments. Journal of Intelligent 8 Robotic Systems 86, 3–4 (2017), 617--639.Google Scholar
- Jonathan Crespo, Jose Carlos Castillo, Oscar Mozos, and Ramón Barber. 2020. Semantic information for robot navigation: A survey. Applied Sciences 10, 2 (2020), 497.Google ScholarCross Ref
- Matthew Crosby, Ronald P. A. Petrick, Francesco Rovida, and Volker Krueger. 2017. Integrating mission and task planning in an industrial robotics framework. In Proceedings of the 27th International Conference on Automated Planning and Scheduling.Google Scholar
- Henning Deeken, Thomas Wiemann, and Joachim Hertzberg. 2018. Grounding semantic maps in spatial databases. Robotics and Autonomous Systems 105 (2018), 146--165.Google ScholarCross Ref
- Saadia Dhouib, Nicolas Du Lac, Jean-Loup Farges, Sébastien Gerard, Miniar Hemaissia-Jeannin, Juan Lahera-Perez, Stéphane Millet, Bruno Patin, and Serge Stinckwich. 2011. Control architecture concepts and properties of an ontology devoted to exchanges in mobile robotics. In Proceedings of the 6th National Conference on Control Architectures of Robot. 1--25.Google Scholar
- Hugh Durrant-Whyte and Tim Bailey. 2006. Simultaneous localization and mapping: Part I. Proceedings of the IEEE Robotics Automation Magazine 13, 2, 99--110.Google ScholarCross Ref
- Mohamad Eid, Ramiro Liscano, and Abdulmotaleb El Saddik. 2007. A universal ontology for sensor networks data. In Proceedings of the IEEE International Conference on Computational Intelligence for Measurement Systems and Applications. 59--62.Google ScholarCross Ref
- R. Gayathri and V. Uma. 2018. Ontology based knowledge representation technique, domain modeling languages and planners for robotic path planning: A survey. ICT Express 4, 2 (2018), 69--74.Google ScholarCross Ref
- Oguzhan Guclu and Ahmet Burak Can. 2019. Fast and effective loop closure detection to improve SLAM performance. Journal of Intelligent 8 Robotic Systems 93, 3 (2019), 495--517.Google ScholarDigital Library
- Tamás Haidegger, Marcos Barreto, Paulo Gonçalves, Maki K. Habib, Sampath Kumar Veera Ragavan, Howard Li, Alberto Vaccarella, Roberta Perrone, and Edson Prestes. 2013. Applied ontologies and standards for service robots. Robotics and Autonomous Systems 61, 11 (2013), 1215--1223.Google ScholarDigital Library
- José A. Castellanos, Henry Carrillo, and Ian Reid. 2012. On the comparison of uncertainty criteria for active SLAM. In Proceedings of the IEEE International Conference on Robotics and Automation. 2080--2087.Google Scholar
- Félix Ingrand and Malik Ghallab. 2017. Deliberation for autonomous robots: A survey. Artificial Intelligence 247 (2017), 10--44.Google ScholarDigital Library
- Graham Klyne and Jeremy J. Carroll. 2004. Resource description framework (RDF): Concepts and abstract syntax. Retrieved from https://www.w3.org/TR/2004/REC-rdf-concepts-20040210/.Google Scholar
- Ioannis Kostavelis and Antonios Gasteratos. 2015. Semantic mapping for mobile robotics tasks: A survey. Robotics and Autonomous Systems 66 (2015), 86--103.Google ScholarDigital Library
- Ruijiao Li, Lai Wei, Dongbing Gu, Huosheng Hu, and Klaus D. McDonald-Maier. 2013. Multi-layered map based navigation and interaction for an intelligent wheelchair. In Proceedings of the IEEE International Conference on Robotics and Biomimetics (ROBIO). 115--120.Google Scholar
- G. H. Lim, I. H. Suh, and H. Suh. 2011. Ontology-based unified robot knowledge for service robots in indoor environments. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 41, 3 (May 2011), 492--509.Google ScholarDigital Library
- Oscar Martınez Mozos, Patric Jensfelt, Hendrik Zender, Geert-Jan M. Kruijff, and Wolfram Burgard. 2007. From labels to semantics: An integrated system for conceptual spatial representations of indoor environments for mobile robots. In Proceedings of the ICRA Workshop: Semantic Information in Robotics.Google Scholar
- Dejan Pangercic, Benjamin Pitzer, Moritz Tenorth, and Michael Beetz. 2012. Semantic object maps for robotic housework - Representation, acquisition and use. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems. 4644--4651.Google ScholarCross Ref
- David Paulius and Yu Sun. 2018. A survey of knowledge representation and retrieval for learning in service robotics. Arxiv Preprint Arxiv:1807.02192 (2018).Google Scholar
- Liam Paull, Gaetan Severac, Guilherme V. Raffo, Julian Mauricio Angel, Harold Boley, Phillip J. Durst, Wendell Gray, Maki Habib, Bao Nguyen, S. Veera Ragavan, et al. 2012. Towards an ontology for autonomous robots. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems. 1359--1364.Google ScholarCross Ref
- Edson Prestes, Joel Luis Carbonera, Sandro Rama Fiorini, Vitor A. M. Jorge, Mara Abel, Raj Madhavan, Angela Locoro, Paulo Goncalves, Marcos E. Barreto, Maki Habib, et al. 2013. Towards a core ontology for robotics and automation. Robotics and Autonomous Systems 61, 11 (2013), 1193--1204.Google ScholarDigital Library
- Andrzej Pronobis and Patric Jensfelt. 2011. Multi-modal semantic mapping. In Proceedings of the RSS Workshop on Grounding Human-Robot Dialog for Spatial Tasks, Los Angeles, CA, USA.Google Scholar
- Francisco Ramos, Andrés S. Vázquez, Raúl Fernández, and Alberto Olivares-Alarcos. 2018. Ontology based design, control and programming of modular robots. Integrated Computer-Aided Engineering 25, 2 (2018), 173--192.Google ScholarCross Ref
- Luis Riazuelo, Moritz Tenorth, Daniel Di Marco, Marta Salas, Dorian Gálvez-López, Lorenz Mösenlechner, Lars Kunze, Michael Beetz, Juan D. Tardós, Luis Montano, et al. 2015. RoboEarth semantic mapping: A cloud enabled knowledge-based approach. IEEE Transactions on Automation Science and Engineering 12, 2 (2015), 432--443.Google ScholarCross Ref
- María L. Rodríguez-Arévalo, José Neira, and José A. Castellanos. 2018. On the importance of uncertainty representation in active SLAM. Proceedings of the IEEE Transactions on Robotics 34, 3 (2018), 829--834.Google ScholarCross Ref
- Zeyn Saigol, Bram Ridder, Minlue Wang, Richard Dearden, Maria Fox, Nick Hawes, David M. Lane, and Derek Long. 2015. Efficient search for known objects in unknown environments using autonomous indoor robots. In Proceedings of the IROS Workshop on Task Planning for Intelligent Robots in Service and Manufacturing.Google Scholar
- Craig Schlenoff and Elena Messina. 2005. A robot ontology for urban search and rescue. In Proceedings of the ACM Workshop on Research in Knowledge Representation for Autonomous Systems (KRAS’05). New York, NY, 27--34.Google ScholarDigital Library
- Muhammad Sualeh and Gon-Woo Kim. 2019. Simultaneous localization and mapping in the epoch of semantics: A survey. International Journal of Control, Automation and Systems 17, 3 (2019), 1--14.Google ScholarCross Ref
- Il Hong Suh, Gi Hyun Lim, Wonil Hwang, Hyowon Suh, Jung-Hwa Choi, and Young-Tack Park. 2007. Ontology-based multi-layered robot knowledge framework (OMRKF) for robot intelligence. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems. 429--436.Google Scholar
- Xiaolei Sun, Yu Zhang, and Jing Chen. 2019. High-level smart decision making of a robot based on ontology in a search and rescue scenario. Future Internet 11, 11 (2019), 230.Google ScholarCross Ref
- Moritz Tenorth and Michael Beetz. 2013. KnowRob: A knowledge processing infrastructure for cognition-enabled robots. The International Journal of Robotics Research 32, 5 (2013), 566--590.Google ScholarDigital Library
- Sebastian Thrun. 2003. Exploring artificial intelligence in the new millennium. Morgan Kaufmann Publishers Inc., San Francisco, CA, Chapter Robotic Mapping: A Survey, 1--35.Google Scholar
- Tingqi Wang and Qijun Chen. 2011. Object semantic map representation for indoor mobile robots. In Proceedings of the International Conference on System Science and Engineering. 309--313.Google ScholarCross Ref
- Hao Wu, Guo-hui Tian, Yan Li, Feng-yu Zhou, and Peng Duan. 2014. Spatial semantic hybrid map building and application of mobile service robot. Robotics and Autonomous Systems 62, 6 (2014), 923--941.Google ScholarDigital Library
- Kai M. Wurm, Armin Hornung, Maren Bennewitz, Cyrill Stachniss, and Wolfram Burgard. 2010. OctoMap: A probabilistic, flexible, and compact 3D map representation for robotic systems. In Proceedings of the ICRA Workshop on Best Practice in 3D Perception and Modeling for Mobile Manipulation, Vol. 2.Google Scholar
- Stefan Zander, Nadia Ahmed, and Matthias T. Frank. 2016. A survey about the usage of semantic technologies for the description of robotic components and capabilities. In Proceedings of the 1st International Workshop on Science, Application and Methods in Industry 4.0 co-located with (i-KNOW 2016). Graz, Austria.Google Scholar
- Liang Zhao, Shoudong Huang, and Gamini Dissanayake. 2019. Linear SLAM: Linearising the SLAM problems using submap joining. Automatica 100 (2019), 231--246.Google ScholarCross Ref
Index Terms
A Survey of Ontologies for Simultaneous Localization and Mapping in Mobile Robots
Recommendations
A categorization of simultaneous localization and mapping knowledge for mobile robots
SAC '20: Proceedings of the 35th Annual ACM Symposium on Applied ComputingAutonomous robots are playing important roles in academic, technological, and scientific activities. Thus, their behavior is getting more complex. The main tasks of autonomous robots include mapping an environment and localize themselves. These tasks ...
Simultaneous Localization and Mapping Based on μ+1-Evolution Strategy for Mobile Robots
ICIRA 2015: Proceedings of the 8th International Conference on Intelligent Robotics and Applications - Volume 9246Simultaneous Localization and Mapping SLAM is one of the most important capabilities for autonomous mobile robots, and many researches have been proposed demonstrating the effective SLAM methods. However, these SLAM methods sometimes require assumptions ...
Multilingual Mapping Reconciliation between English-French Biomedical Ontologies
WIMS '16: Proceedings of the 6th International Conference on Web Intelligence, Mining and SemanticsEven if multilingual ontologies are now more common, for historical reasons, in the biomedical domain, many ontologies or terminologies have been translated from one natural language to another resulting in two potentially aligned ontologies but with ...
Comments