ABSTRACT
Aiming at the demand for map expression in the human-robot co-existing environments, a multi-layer map including semantic grid map, semantic topological map and semantic concept map is proposed and constructed. Firstly, 2D LIDAR and RGB-D sensors are used to construct object semantic grid map combined with SLAM and object semantic segmentation method. Semantic topological map is then constructed using virtual door detection and Bayesian estimation method based on room and object containment relationships. Finally, according to the semantic grid and the semantic topological map, a seven-step ontology creation method is used to build a semantic concept map. The effectiveness of the proposed multi-layer map is verified by testing in multiple scenarios.
- Thrun S. Robotic mapping: A survey[J]. Exploring Artificial Intelligence in the New Millenium, 2002(3): 1-35.Google Scholar
- Zender H, Mozos O M, Jensfelt P, Conceptual spatial representations for indoor mobile robots[J]. Robotics and Autonomous Systems, 2008, 56(6): 493-502.Google ScholarDigital Library
- Lim G H, Suh I H, Suh H. Ontology-based unified robot knowledge for service robots in indoor environments[J]. IEEE Transactions on Systems, Man and Cybernetics, Part A (Systems and Humans), 2011, 41(3):492-509.Google ScholarDigital Library
- Pronobis A, Jensfelt P. Large-scale semantic mapping and reasoning with heterogeneous modalities[C]//2012 IEEE international conference on robotics and automation. IEEE, 2012: 3515-3522.Google Scholar
- Qi X, Wang W, Liao Z, Object Semantic Grid Mapping with 2D LiDAR and RGB-D Camera for Domestic Robot Navigation[J]. Applied Sciences, 2020, 10(17):5782.Google ScholarCross Ref
- Qi X, Wang W, Zhang X, Indoor topological map building with virtual door detection[J]. Journal of Jilin University (Engineering and Technology Edition), 2020, v.50; No.209(03):258-264.Google Scholar
- Qi X, Wang W, Wang L, Semantic topological map building with object semantic grid map[J]. Journal of Jilin University (Engineering and Technology Edition), 2022, DOI: 10.13229/j.cnki.jdxbgxb20210623.Google Scholar
- Hess W, Kohler D, Rapp H, Real-time loop closure in 2D LIDAR SLAM[C]//Robotics and Automation (ICRA), 2016 IEEE International Conference on. IEEE, 2016: 1271-1278.Google Scholar
- He K, Gkioxari G, Dollár P, Mask RCNN. arXiv e-prints, Article. arXiv 2017, arXiv:1703.06870.Google Scholar
- Ruiz-Sarmiento J R, Galindo C, Gonzalez-Jimenez J. Robot@Home, a robotic dataset for semantic mapping of home environments[J]. International journal of robotics research. 2017, 36, 131–141.Google ScholarDigital Library
- Decker S, Melnik S, Van Harmelen F, The semantic web: The roles of XML and RDF[J]. IEEE Internet computing, 2000, 4(5):63-73Google ScholarDigital Library
Index Terms
- Expression and Construction of a Multi-layer Map for Indoor Human-Robot Co-existing Environments
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