This review article is an attempt to survey all recent AI based techniques used to deal with
major functions in This review paper presents a comprehensive overview of end-to-end …

Simultaneous Localization and Mapping (SLAM) stands as one of the critical challenges in
robot navigation. A SLAM system often consists of a front-end component for motion …

ABSTRACT Inertial Measurement Units (IMU) are commonly used in inertial attitude
estimation from engineering to medical sciences. There may be disturbances and high …

Control of an ego vehicle for Autonomous Driving (AD) requires an accurate definition of its
state. Implementation of various model-based Kalman Filtering (KF) techniques for state …

This paper presents a novel end-to-end deep learning framework for real-time inertial
attitude estimation using 6DoF IMU measurements. Inertial Measurement Units are widely …

Visual-inertial odometry (VIO) is the pose estimation backbone for most AR/VR and
autonomous robotic systems today, in both academia and industry. However, these systems …

Monocular visual-inertial odometry (VIO) is a critical problem in robotics and autonomous
driving. Traditional methods solve this problem based on filtering or optimization. While …

Securing reliable navigation in complex, Global Navigation Satellite Systems (GNSS)
denied terrains is critical in maintaining the situational awareness in infrastructurefree …

As a basic and indispensable module in Simultaneously Localization And Mapping (SLAM),
sensor ego-motion estimation is widely used in robotics. The traditional multi-view geometry …

In this thesis, we systematically study the integration of deep learning and simultaneous
localization and mapping (SLAM) and advance the research frontier by making the following …