ביצועי ניווט משופרים באמצעות עקיבת מאפיינים

צחי אביב
עבודה לקראת תואר מגיסטר תחת הנחייתם של פרופ' פ. גורפיל וד"ר ה. רוטשטיין
הפקולטה להנדסת אוירונוטיקה וחלל
טכניון - מוסד טכנולוגי לישראל

Inertial navigation is ubiquitous; however, it tends diverge due to imperfections in the inertial sensors, resulting in growing position and attitude errors. Thus, it is a common practice to aid the inertial navigation using external sensors. In the current research, we develop a method for aiding the inertial navigation using optical information captured by an onboard wide field-of-view (FOV) camera.

The basic concept is to use a sequence of frames captured by the camera along the platform trajectory. Once detecting the same features in a number of sequential frames, it is possible to use the feature motion across the detector matrix as the estimation innovation. A key advantage of this concept is the fact there is no need of any a priori information regarding the scene.

Due to the problem nonlinearity, there are no existing closed-form solutions for the aiding process, and the common estimators used are the extended Kalman filter (EKF) or bundle adjustment, which both require restrictive assumptions. In this research, we solve the aiding problem from a maximum likelihood point of view, and develop an optimal estimator under a Gaussian assumption, which enables to fuse inertial measurements with the multiple feature optical measurements. The performance of the new method is evaluated in a number of realistic scenarios.

הסמינר יינתן בעברית

רביעי, 18-06-2014, 16:30 (התכנסות בשעה 16:00)

כיתת הספריה, קומה ראשונה

כיבוד קל יוגש לפני תחילת הסמינר


Inertial Navigation Aiding Using Multiple View Feature Matching