This paper is an overview to Visual Simultaneous Localization and Map** (V-SLAM). We
discuss the basic definitions in the SLAM and vision system fields and provide a review of …

Visual SLAM (VSLAM) has been develo** rapidly due to its advantages of low-cost
sensors, the easy fusion of other sensors, and richer environmental information. Traditional …

Navigation/positioning systems have become critical to many applications, such as
autonomous driving, Internet of Things (IoT), Unmanned Aerial Vehicle (UAV), and smart …

Depth information is important for autonomous systems to perceive environments and
estimate their own state. Traditional depth estimation methods, like structure from motion …

In current decades, significant advancements in robotics engineering and autonomous
vehicles have improved the requirement for precise depth measurements. Depth estimation …

We propose a novel monocular visual odometry (VO) system called UnDeepVO in this
paper. UnDeepVO is able to estimate the 6-DoF pose of a monocular camera and the depth …

Flying robots require a combination of accuracy and low latency in their state estimation in
order to achieve stable and robust flight. However, due to the power and payload constraints …

The representation of geometry in real-time 3D perception systems continues to be a critical
research issue. Dense maps capture complete surface shape and can be augmented with …

In this work, we propose a VAE-LSTM hybrid model as an unsupervised approach for
anomaly detection in time series. Our model utilizes both a VAE module for forming robust …

Inertial sensors play a pivotal role in indoor localization, which in turn lays the foundation for
pervasive personal applications. However, low-cost inertial sensors, as commonly found in …