Social and Robust Navigation for Indoor Robots Based on Object Semantic Grid and Topological Map
| العنوان: | Social and Robust Navigation for Indoor Robots Based on Object Semantic Grid and Topological Map |
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| المؤلفون: | Xianyu Qi, Wei Wang, Ziwei Liao, Jiadong Zhang |
| المصدر: | Applied Sciences, Vol 10, Iss 8991, p 8991 (2020) Applied Sciences Volume 10 Issue 24 |
| بيانات النشر: | MDPI AG, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | 0209 industrial biotechnology, Computer science, 02 engineering and technology, lcsh:Technology, lcsh:Chemistry, 020901 industrial engineering & automation, indoor robot navigation, Robustness (computer science), object sematic grid and topological map, General Materials Science, Computer vision, Topological map, Motion planning, Instrumentation, lcsh:QH301-705.5, Fluid Flow and Transfer Processes, business.industry, lcsh:T, Process Chemistry and Technology, General Engineering, Navigation system, natural language interaction, 021001 nanoscience & nanotechnology, Object (computer science), lcsh:QC1-999, Computer Science Applications, auxiliary navigation point, Semantic grid, segmented global path planning, lcsh:Biology (General), lcsh:QD1-999, lcsh:TA1-2040, Robot, Artificial intelligence, 0210 nano-technology, business, lcsh:Engineering (General). Civil engineering (General), Natural language, lcsh:Physics |
| الوصف: | For the indoor navigation of service robots, human&ndash robot interaction and adapting to the environment still need to be strengthened, including determining the navigation goal socially, improving the success rate of passing doors, and optimizing the path planning efficiency. This paper proposes an indoor navigation system based on object semantic grid and topological map, to optimize the above problems. First, natural language is used as a human&ndash robot interaction form, from which the target room, object, and spatial relationship can be extracted by using speech recognition and word segmentation. Then, the robot selects the goal point from the target space by object affordance theory. To improve the navigation success rate and safety, we generate auxiliary navigation points on both sides of the door to correct the robot trajectory. Furthermore, based on the topological map and auxiliary navigation points, the global path is segmented into each topological area. The path planning algorithm is carried on respectively in every room, which significantly improves the navigation efficiency. This system has demonstrated to support autonomous navigation based on language interaction and significantly improve the safety, efficiency, and robustness of indoor robot navigation. Our system has been successfully tested in real domestic environments. |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 2076-3417 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5b132684ec66fde4df302aaf741ccf6Test https://www.mdpi.com/2076-3417/10/24/8991Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....d5b132684ec66fde4df302aaf741ccf6 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 20763417 |
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