DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Kim, Jong-Hwan | - |
dc.contributor.advisor | 김종환 | - |
dc.contributor.author | Lee, Kanghee | - |
dc.date.accessioned | 2019-09-04T02:40:54Z | - |
dc.date.available | 2019-09-04T02:40:54Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=843774&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/266743 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2019.2,[iv, 34 p. :] | - |
dc.description.abstract | Autonomous driving technology has become an interesting issue for the automobile industry with advances in localization, obstacle detection, and the Internet of Things (IoT) technology. In order to make a safe self-driving, the vehicle must be able to estimate the precise pose of the vehicle body on the road. GPS is a sensor used generally to measure the absolute pose, but the bunch of buildings, tunnel or any indoor place can block the satellite microwave signals. Recently, many research validated the pose estimation method using other sensors such as wheel encoders, camera, and IMU for GPS-denied environments. In this paper, we proposed a compensation method of a monocular camera and in-vehicle sensors for robust localization. The method overcomes a scale ambiguity issue of monocular visual odometry and angular velocity measurement error of wheel odometry by using in-vehicle sensors. Furthermore, we proposed the fusion method between a monocular camera and in-vehicle sensors, which based on Extended Kalman Filter. We validate the proposed algorithm on the SKT real road dataset, which includes loop road, highway, and sloped road. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Monocular Visual In-Vehicle sensors Odometry (MVIVO)▼asensor fusion▼ain-vehicle sensors▼amonocular camera▼aGPS-denied environment▼apose estimation | - |
dc.subject | 단안 카메라-차량 내부 센서 오도메트리(MVIVO)▼a센서 융합▼a차량 내부 센서▼a단안 카메라▼aGPS 오작동 환경▼a주행 거리 측정 | - |
dc.title | Sensor fusion-based robust navigation in the GPS-denied environment using monocular camera and in-vehicle sensors | - |
dc.title.alternative | 단안 카메라와 차량 내부 센서를 이용한 GPS 오작동 환경에서 강인한 주행거리 측정 기반 센서 퓨전 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전기및전자공학부, | - |
dc.contributor.alternativeauthor | 이강희 | - |
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