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The integration of GPS/BDS real-time kinematic positioning and visual–inertial odometry based on smartphones / Zun Niu in ISPRS International journal of geo-information, vol 10 n° 10 (October 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 10 (October 2021) . - n° 699 Titre : The integration of GPS/BDS real-time kinematic positioning and visual–inertial odometry based on smartphones Type de document : Article/Communication Auteurs : Zun Niu, Auteur ; Fugui Guo, Auteur ; Qiangqiang Shuai, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 699 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] C++ [Termes IGN] centrale inertielle [Termes IGN] filtre de Kalman [Termes IGN] format RINEX [Termes IGN] odomètre [Termes IGN] positionnement cinématique en temps réel [Termes IGN] positionnement par BeiDou [Termes IGN] positionnement par GNSS [Termes IGN] précision du positionnement [Termes IGN] programmation informatique [Termes IGN] robot [Termes IGN] téléphone intelligent [Termes IGN] vision par ordinateur Résumé : (auteur) The real-time kinematic positioning technique (RTK) and visual–inertial odometry (VIO) are both promising positioning technologies. However, RTK degrades in GNSS-hostile areas, where global navigation satellite system (GNSS) signals are reflected and blocked, while VIO is affected by long-term drift. The integration of RTK and VIO can improve the accuracy and robustness of positioning. In recent years, smartphones equipped with multiple sensors have become commodities and can provide measurements for integrating RTK and VIO. This paper verifies the feasibility of integrating RTK and VIO using smartphones, and we propose an improved algorithm to integrate RTK and VIO with better performance. We began by developing an Android smartphone application for data collection and then wrote a Python program to convert the data to a robot operating system (ROS) bag. Next, we established two ROS nodes to calculate the RTK results and accomplish the integration. Finally, we conducted experiments in urban areas to assess the integration of RTK and VIO based on smartphones. The results demonstrate that the integration improves the accuracy and robustness of positioning and that our improved algorithm reduces altitude deviation. Our work can aid navigation and positioning research, which is the reason why we open source the majority of the codes at our GitHub. Numéro de notice : A2021-800 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10100699 Date de publication en ligne : 14/10/2021 En ligne : https://doi.org/10.3390/ijgi10100699 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98852 [article]