Intelligent unmanned systems have important applications, such as pesticide-spraying in
agriculture, robot-based warehouse management systems, and missile-firing drones. The …

Dense optical flow estimation plays a key role in many robotic vision tasks. In the past few
years, with the advent of deep learning, we have witnessed great progress in optical flow …

Recent studies in radar-based navigation present promising navigation performance using
scanning radars. These scanning radar-based odometry methods are mostly feature-based; …

Convolutional neural networks (CNNs) have enabled the state-of-the-art performance in
many computer vision tasks. However, little effort has been devoted to establishing …

Most of the existing visual SLAM methods heavily rely on a static world assumption and
easily fail in dynamic environments. Some recent works eliminate the influence of dynamic …

In this paper we propose a method to achieve relative positioning and tracking of a target by
a quadcopter using Ultra-wideband (UWB) ranging sensors, which are strategically installed …

Human action recognition is an emerging goal of computer vision with several applications
such as video surveillance and human-computer interaction. Despite many attempts to …

When mobile robots are working in indoor unknown environments, the surrounding scenes
are mainly low texture or repeating texture. This means that image features are easily lost …

Optical flow is considered an important step in many computer vision applications. Some
optical flow estimation approaches are mainly based on correlation, gradient and frequency …

As an essential component of visual simultaneous localization and mapping (SLAM), place
recognition is crucial for robot navigation and autonomous driving. Existing methods often …