{"title":"基于时移IMU预积分的增量视觉惯性初始化时序标定","authors":"Bruno Petit, Richard Guillemard, V. Gay-Bellile","doi":"10.1109/3DV50981.2020.00027","DOIUrl":null,"url":null,"abstract":"Tightly coupled Visual-Inertial SLAM (VISLAM) algorithms are now state of the art approaches for indoor localization. There are many implementations of VISLAM, like filter-based and non-linear optimization based algorithms. They all require an accurate temporal alignment between sensors clock and an initial IMU state gyroscope and accelerometer biases value, gravity direction and initial velocity) for precise localization. In this paper we propose an initialization procedure of VISLAM that estimates simultaneously IMU-camera temporal calibration and the initial IMU state. To this end, the concept of Time Shifted IMU Preintegration} (TSIP) measurements is introduced. an interpolation of IMU preintegration that takes into account the effect of sensors clock misalignment. These TSIP measurements are included along with visual odometry measurements in a graph that is incrementally optimized. It results in a real time, accurate and robust initialization for VISLAM as demonstrated in the experiments on real data.","PeriodicalId":293399,"journal":{"name":"2020 International Conference on 3D Vision (3DV)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Time Shifted IMU Preintegration for Temporal Calibration in Incremental Visual-Inertial Initialization\",\"authors\":\"Bruno Petit, Richard Guillemard, V. Gay-Bellile\",\"doi\":\"10.1109/3DV50981.2020.00027\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Tightly coupled Visual-Inertial SLAM (VISLAM) algorithms are now state of the art approaches for indoor localization. There are many implementations of VISLAM, like filter-based and non-linear optimization based algorithms. They all require an accurate temporal alignment between sensors clock and an initial IMU state gyroscope and accelerometer biases value, gravity direction and initial velocity) for precise localization. In this paper we propose an initialization procedure of VISLAM that estimates simultaneously IMU-camera temporal calibration and the initial IMU state. To this end, the concept of Time Shifted IMU Preintegration} (TSIP) measurements is introduced. an interpolation of IMU preintegration that takes into account the effect of sensors clock misalignment. These TSIP measurements are included along with visual odometry measurements in a graph that is incrementally optimized. It results in a real time, accurate and robust initialization for VISLAM as demonstrated in the experiments on real data.\",\"PeriodicalId\":293399,\"journal\":{\"name\":\"2020 International Conference on 3D Vision (3DV)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on 3D Vision (3DV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/3DV50981.2020.00027\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on 3D Vision (3DV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/3DV50981.2020.00027","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Time Shifted IMU Preintegration for Temporal Calibration in Incremental Visual-Inertial Initialization
Tightly coupled Visual-Inertial SLAM (VISLAM) algorithms are now state of the art approaches for indoor localization. There are many implementations of VISLAM, like filter-based and non-linear optimization based algorithms. They all require an accurate temporal alignment between sensors clock and an initial IMU state gyroscope and accelerometer biases value, gravity direction and initial velocity) for precise localization. In this paper we propose an initialization procedure of VISLAM that estimates simultaneously IMU-camera temporal calibration and the initial IMU state. To this end, the concept of Time Shifted IMU Preintegration} (TSIP) measurements is introduced. an interpolation of IMU preintegration that takes into account the effect of sensors clock misalignment. These TSIP measurements are included along with visual odometry measurements in a graph that is incrementally optimized. It results in a real time, accurate and robust initialization for VISLAM as demonstrated in the experiments on real data.