Mobile robots lack a driver or a pilot and, thus, should be able to detect obstacles
autonomously. This paper reviews various image-based obstacle detection techniques …

Self-driving cars are a hot research topic in science and technology, which has a great
influence on social and economic development. Deep learning is one of the current key …

As an essential component for many autonomous driving and robotic activities such as ego-
motion estimation, obstacle avoidance and scene understanding, monocular depth …

This paper presents our method for enabling a UAV quadrotor, equipped with a monocular
camera, to autonomously avoid collisions with obstacles in unstructured and unknown …

Abstract In recent years, Unmanned Aerial Vehicles (UAVs) are widely utilized in precision
agriculture, such as tree plantations. Due to limited intelligence, these UAVs can only …

Depth prediction from single image is a challenging task due to the intra scale ambiguity and
unavailability of prior information. The prediction of an unambiguous depth from single RGB …

RGB-D data is essential for solving many problems in computer vision. Hundreds of public
RGB-D datasets containing various scenes, such as indoor, outdoor, aerial, driving, and …

In this work, we propose a method for estimating depth for an image of a monocular camera
in order to avoid a collision for the autonomous flight of a drone. The highest flight speed of a …

Visual obstacle discovery is a key step towards autonomous navigation of indoor mobile
robots. Successful solutions have many applications in multiple scenes. One of the …

Depth estimation from a single RGB image has attracted great interest in autonomous
driving and robotics. State-of-the-art methods are usually designed on top of complex and …