An Optimized Tightly-Coupled VIO Design on the Basis of the Fused Point and Line Features for Patrol Robot Navigation
The development and maturation of simultaneous localization and mapping (SLAM) in robotics opens the door to the application of a visual inertial odometry (VIO) to the robot navigation system. For a patrol robot with no available Global Positioning System (GPS) support, the embedded VIO components,...
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MDPI AG
2019-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/9/2004 |
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| author | Linlin Xia Qingyu Meng Deru Chi Bo Meng Hanrui Yang |
| author_facet | Linlin Xia Qingyu Meng Deru Chi Bo Meng Hanrui Yang |
| author_sort | Linlin Xia |
| collection | DOAJ |
| description | The development and maturation of simultaneous localization and mapping (SLAM) in robotics opens the door to the application of a visual inertial odometry (VIO) to the robot navigation system. For a patrol robot with no available Global Positioning System (GPS) support, the embedded VIO components, which are generally composed of an Inertial Measurement Unit (IMU) and a camera, fuse the inertial recursion with SLAM calculation tasks, and enable the robot to estimate its location within a map. The highlights of the optimized VIO design lie in the simplified VIO initialization strategy as well as the fused point and line feature-matching based method for efficient pose estimates in the front-end. With a tightly-coupled VIO anatomy, the system state is explicitly expressed in a vector and further estimated by the state estimator. The consequent problems associated with the data association, state optimization, sliding window and timestamp alignment in the back-end are discussed in detail. The dataset tests and real substation scene tests are conducted, and the experimental results indicate that the proposed VIO can realize the accurate pose estimation with a favorable initializing efficiency and eminent map representations as expected in concerned environments. The proposed VIO design can therefore be recognized as a preferred tool reference for a class of visual and inertial SLAM application domains preceded by no external location reference support hypothesis. |
| first_indexed | 2024-04-14T04:31:38Z |
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| id | doaj.art-5faee81a99f742119c4e15cc7b71bca4 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T04:31:38Z |
| publishDate | 2019-04-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj.art-5faee81a99f742119c4e15cc7b71bca42022-12-22T02:12:01ZengMDPI AGSensors1424-82202019-04-01199200410.3390/s19092004s19092004An Optimized Tightly-Coupled VIO Design on the Basis of the Fused Point and Line Features for Patrol Robot NavigationLinlin Xia0Qingyu Meng1Deru Chi2Bo Meng3Hanrui Yang4School of Automation Engineering, Northeast Electric Power University, Jilin 132012, ChinaSchool of Automation Engineering, Northeast Electric Power University, Jilin 132012, ChinaSchool of Automation Engineering, Northeast Electric Power University, Jilin 132012, ChinaSchool of Computer Science, Northeast Electric Power University, Jilin 132012, ChinaSchool of Automation Engineering, Northeast Electric Power University, Jilin 132012, ChinaThe development and maturation of simultaneous localization and mapping (SLAM) in robotics opens the door to the application of a visual inertial odometry (VIO) to the robot navigation system. For a patrol robot with no available Global Positioning System (GPS) support, the embedded VIO components, which are generally composed of an Inertial Measurement Unit (IMU) and a camera, fuse the inertial recursion with SLAM calculation tasks, and enable the robot to estimate its location within a map. The highlights of the optimized VIO design lie in the simplified VIO initialization strategy as well as the fused point and line feature-matching based method for efficient pose estimates in the front-end. With a tightly-coupled VIO anatomy, the system state is explicitly expressed in a vector and further estimated by the state estimator. The consequent problems associated with the data association, state optimization, sliding window and timestamp alignment in the back-end are discussed in detail. The dataset tests and real substation scene tests are conducted, and the experimental results indicate that the proposed VIO can realize the accurate pose estimation with a favorable initializing efficiency and eminent map representations as expected in concerned environments. The proposed VIO design can therefore be recognized as a preferred tool reference for a class of visual and inertial SLAM application domains preceded by no external location reference support hypothesis.https://www.mdpi.com/1424-8220/19/9/2004tightly-coupled VIOSLAMfused point and line feature matchingpose estimatessimplified initialization strategypatrol robotmap representation |
| spellingShingle | Linlin Xia Qingyu Meng Deru Chi Bo Meng Hanrui Yang An Optimized Tightly-Coupled VIO Design on the Basis of the Fused Point and Line Features for Patrol Robot Navigation Sensors tightly-coupled VIO SLAM fused point and line feature matching pose estimates simplified initialization strategy patrol robot map representation |
| title | An Optimized Tightly-Coupled VIO Design on the Basis of the Fused Point and Line Features for Patrol Robot Navigation |
| title_full | An Optimized Tightly-Coupled VIO Design on the Basis of the Fused Point and Line Features for Patrol Robot Navigation |
| title_fullStr | An Optimized Tightly-Coupled VIO Design on the Basis of the Fused Point and Line Features for Patrol Robot Navigation |
| title_full_unstemmed | An Optimized Tightly-Coupled VIO Design on the Basis of the Fused Point and Line Features for Patrol Robot Navigation |
| title_short | An Optimized Tightly-Coupled VIO Design on the Basis of the Fused Point and Line Features for Patrol Robot Navigation |
| title_sort | optimized tightly coupled vio design on the basis of the fused point and line features for patrol robot navigation |
| topic | tightly-coupled VIO SLAM fused point and line feature matching pose estimates simplified initialization strategy patrol robot map representation |
| url | https://www.mdpi.com/1424-8220/19/9/2004 |
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