{"title":"多旋翼飞行器仅用惯性传感器导航的多短跳方法","authors":"Xiangyu Wu, M. Mueller","doi":"10.1109/ICRA40945.2020.9196610","DOIUrl":null,"url":null,"abstract":"In certain challenging environments, such as inside buildings on fire, the main sensors (e.g. cameras, LiDARs and GPS systems) used for multicopter localization can become unavailable. Direct integration of the inertial navigation sensors (the accelerometer and rate gyroscope), is however unaffected by external disturbances, but the rapid error accumulation quickly makes a naive application of such a strategy feasible only for very short durations. In this work we propose a motion strategy for reducing the inertial navigation state estimation error of multicopters. The proposed strategy breaks a long duration flight into multiple short duration hops between which the vehicle remains stationary on the ground. When the vehicle is stationary, zero-velocity pseudo-measurements are introduced to an extended Kalman Filter to reduce the state estimation error. We perform experiments for closed-loop control of a multicopter for evaluation. The mean absolute position estimation error was 3.4% over a total flight distance of 5m in the experiments. The results showed a 80% reduction compared to the standard inertial navigation method without using this strategy. In addition, an additional experiment with total flight distance of 10m is conducted to demonstrate the ability of this method to navigate a multicopter in real-world environment. The final trajectory tracking error was 3% of the total flight distance.","PeriodicalId":6859,"journal":{"name":"2020 IEEE International Conference on Robotics and Automation (ICRA)","volume":"109 1","pages":"8559-8565"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Using multiple short hops for multicopter navigation with only inertial sensors\",\"authors\":\"Xiangyu Wu, M. Mueller\",\"doi\":\"10.1109/ICRA40945.2020.9196610\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In certain challenging environments, such as inside buildings on fire, the main sensors (e.g. cameras, LiDARs and GPS systems) used for multicopter localization can become unavailable. Direct integration of the inertial navigation sensors (the accelerometer and rate gyroscope), is however unaffected by external disturbances, but the rapid error accumulation quickly makes a naive application of such a strategy feasible only for very short durations. In this work we propose a motion strategy for reducing the inertial navigation state estimation error of multicopters. The proposed strategy breaks a long duration flight into multiple short duration hops between which the vehicle remains stationary on the ground. When the vehicle is stationary, zero-velocity pseudo-measurements are introduced to an extended Kalman Filter to reduce the state estimation error. We perform experiments for closed-loop control of a multicopter for evaluation. The mean absolute position estimation error was 3.4% over a total flight distance of 5m in the experiments. The results showed a 80% reduction compared to the standard inertial navigation method without using this strategy. In addition, an additional experiment with total flight distance of 10m is conducted to demonstrate the ability of this method to navigate a multicopter in real-world environment. The final trajectory tracking error was 3% of the total flight distance.\",\"PeriodicalId\":6859,\"journal\":{\"name\":\"2020 IEEE International Conference on Robotics and Automation (ICRA)\",\"volume\":\"109 1\",\"pages\":\"8559-8565\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Robotics and Automation (ICRA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRA40945.2020.9196610\",\"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 IEEE International Conference on Robotics and Automation (ICRA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRA40945.2020.9196610","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using multiple short hops for multicopter navigation with only inertial sensors
In certain challenging environments, such as inside buildings on fire, the main sensors (e.g. cameras, LiDARs and GPS systems) used for multicopter localization can become unavailable. Direct integration of the inertial navigation sensors (the accelerometer and rate gyroscope), is however unaffected by external disturbances, but the rapid error accumulation quickly makes a naive application of such a strategy feasible only for very short durations. In this work we propose a motion strategy for reducing the inertial navigation state estimation error of multicopters. The proposed strategy breaks a long duration flight into multiple short duration hops between which the vehicle remains stationary on the ground. When the vehicle is stationary, zero-velocity pseudo-measurements are introduced to an extended Kalman Filter to reduce the state estimation error. We perform experiments for closed-loop control of a multicopter for evaluation. The mean absolute position estimation error was 3.4% over a total flight distance of 5m in the experiments. The results showed a 80% reduction compared to the standard inertial navigation method without using this strategy. In addition, an additional experiment with total flight distance of 10m is conducted to demonstrate the ability of this method to navigate a multicopter in real-world environment. The final trajectory tracking error was 3% of the total flight distance.