Pedro Lourenço, Bruno J. Guerreiro, P. Batista, P. Oliveira, C. Silvestre
{"title":"Preliminary results on globally asymptotically stable simultaneous localization and mapping in 3-D","authors":"Pedro Lourenço, Bruno J. Guerreiro, P. Batista, P. Oliveira, C. Silvestre","doi":"10.1109/ACC.2013.6580305","DOIUrl":null,"url":null,"abstract":"This paper presents the design, analysis, performance evaluation, and preliminary experimental validation of a globally asymptotically stable (GAS) filter for simultaneous localization and mapping (SLAM) with application to unmanned aerial vehicles (UAVs). The SLAM problem is formulated in a sensor-based framework and modified in such a way that the system structure may be regarded as linear time-varying for observability purposes, from which a Kalman filter with GAS error dynamics follows naturally. The proposed solution includes the estimation of both body-fixed linear velocity and rate-gyro measurement biases. Both simulation results and preliminary experimental results, using an instrumented quadrotor equipped with a RGB-D camera, are included in the paper to illustrate the performance of the algorithm under realistic conditions.","PeriodicalId":145065,"journal":{"name":"2013 American Control Conference","volume":"302 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 American Control Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACC.2013.6580305","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
This paper presents the design, analysis, performance evaluation, and preliminary experimental validation of a globally asymptotically stable (GAS) filter for simultaneous localization and mapping (SLAM) with application to unmanned aerial vehicles (UAVs). The SLAM problem is formulated in a sensor-based framework and modified in such a way that the system structure may be regarded as linear time-varying for observability purposes, from which a Kalman filter with GAS error dynamics follows naturally. The proposed solution includes the estimation of both body-fixed linear velocity and rate-gyro measurement biases. Both simulation results and preliminary experimental results, using an instrumented quadrotor equipped with a RGB-D camera, are included in the paper to illustrate the performance of the algorithm under realistic conditions.