Semantic Information for Robot Navigation: A Survey
There is a growing trend in robotics for implementing behavioural mechanisms based on human psychology, such as the processes associated with thinking. Semantic knowledge has opened new paths in robot navigation, allowing a higher level of abstraction in the representation of information. In contras...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/2/497 |
| _version_ | 1818017999904309248 |
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| author | Jonathan Crespo Jose Carlos Castillo Oscar Martinez Mozos Ramon Barber |
| author_facet | Jonathan Crespo Jose Carlos Castillo Oscar Martinez Mozos Ramon Barber |
| author_sort | Jonathan Crespo |
| collection | DOAJ |
| description | There is a growing trend in robotics for implementing behavioural mechanisms based on human psychology, such as the processes associated with thinking. Semantic knowledge has opened new paths in robot navigation, allowing a higher level of abstraction in the representation of information. In contrast with the early years, when navigation relied on geometric navigators that interpreted the environment as a series of accessible areas or later developments that led to the use of graph theory, semantic information has moved robot navigation one step further. This work presents a survey on the concepts, methodologies and techniques that allow including semantic information in robot navigation systems. The techniques involved have to deal with a range of tasks from modelling the environment and building a semantic map, to including methods to learn new concepts and the representation of the knowledge acquired, in many cases through interaction with users. As understanding the environment is essential to achieve high-level navigation, this paper reviews techniques for acquisition of semantic information, paying attention to the two main groups: human-assisted and autonomous techniques. Some state-of-the-art semantic knowledge representations are also studied, including ontologies, cognitive maps and semantic maps. All of this leads to a recent concept, semantic navigation, which integrates the previous topics to generate high-level navigation systems able to deal with real-world complex situations. |
| first_indexed | 2024-04-14T07:34:19Z |
| format | Article |
| id | doaj.art-cd2f274e235c4cfba677d46938818e59 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-04-14T07:34:19Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-cd2f274e235c4cfba677d46938818e592022-12-22T02:05:45ZengMDPI AGApplied Sciences2076-34172020-01-0110249710.3390/app10020497app10020497Semantic Information for Robot Navigation: A SurveyJonathan Crespo0Jose Carlos Castillo1Oscar Martinez Mozos2Ramon Barber3Higher Technical School of Computer Engineering, UniversityRey Juan Carlos, 28933 Móstoles, SpainDepartment of Systems Engineering and Automation, University Carlos III of Madrid, 28911 Leganés, SpainCentre for Applied Autonomous Sensor Systems, Örebro University, 70182 Örebro, SwedenDepartment of Systems Engineering and Automation, University Carlos III of Madrid, 28911 Leganés, SpainThere is a growing trend in robotics for implementing behavioural mechanisms based on human psychology, such as the processes associated with thinking. Semantic knowledge has opened new paths in robot navigation, allowing a higher level of abstraction in the representation of information. In contrast with the early years, when navigation relied on geometric navigators that interpreted the environment as a series of accessible areas or later developments that led to the use of graph theory, semantic information has moved robot navigation one step further. This work presents a survey on the concepts, methodologies and techniques that allow including semantic information in robot navigation systems. The techniques involved have to deal with a range of tasks from modelling the environment and building a semantic map, to including methods to learn new concepts and the representation of the knowledge acquired, in many cases through interaction with users. As understanding the environment is essential to achieve high-level navigation, this paper reviews techniques for acquisition of semantic information, paying attention to the two main groups: human-assisted and autonomous techniques. Some state-of-the-art semantic knowledge representations are also studied, including ontologies, cognitive maps and semantic maps. All of this leads to a recent concept, semantic navigation, which integrates the previous topics to generate high-level navigation systems able to deal with real-world complex situations.https://www.mdpi.com/2076-3417/10/2/497semantic informationreasoningmobile robotsontologiespath planningcognitive robotics |
| spellingShingle | Jonathan Crespo Jose Carlos Castillo Oscar Martinez Mozos Ramon Barber Semantic Information for Robot Navigation: A Survey Applied Sciences semantic information reasoning mobile robots ontologies path planning cognitive robotics |
| title | Semantic Information for Robot Navigation: A Survey |
| title_full | Semantic Information for Robot Navigation: A Survey |
| title_fullStr | Semantic Information for Robot Navigation: A Survey |
| title_full_unstemmed | Semantic Information for Robot Navigation: A Survey |
| title_short | Semantic Information for Robot Navigation: A Survey |
| title_sort | semantic information for robot navigation a survey |
| topic | semantic information reasoning mobile robots ontologies path planning cognitive robotics |
| url | https://www.mdpi.com/2076-3417/10/2/497 |
| work_keys_str_mv | AT jonathancrespo semanticinformationforrobotnavigationasurvey AT josecarloscastillo semanticinformationforrobotnavigationasurvey AT oscarmartinezmozos semanticinformationforrobotnavigationasurvey AT ramonbarber semanticinformationforrobotnavigationasurvey |