Autonomous vehicles (AV) are expected to improve, reshape, and revolutionize the future of
ground transportation. It is anticipated that ordinary vehicles will one day be replaced with …

Research and development of autonomous mobile robotic solutions that can perform
several active agricultural tasks (pruning, harvesting, mowing) have been growing. Robots …

This work presents a review and discussion of the challenges that must be solved in order to
successfully develop swarms of Micro Air Vehicles (MAVs) for real world operations. From …

Visual simultaneous localization and mapping (SLAM) has attracted high attention over the
past few years. In this paper, a comprehensive survey of the state-of-the-art feature-based …

Simultaneous localization and mapping (SLAM) is a quintessential problem in autonomous
navigation, augmented reality, and virtual reality. In particular, low-power SLAM has gained …

Traditional Simultaneous Localization and Mapping (SLAM)(with loop closure detection), or
Visual Odometry (VO)(without loop closure detection), are based on the static environment …

Subsurface networks include mining tunnels, caves, and the urban underground. Each of
these environments presents a complex setting with significant challenges in exploration …

The goal of this paper is to generate simulations with real-world collision scenarios for
training and testing autonomous vehicles. We use numerous dashcam crash videos …

The purpose of this paper is to present the results of the analysis of the application of Deep
Learning in the railway domain with a particular focus on a train stop operation. The paper …

Modern smartphones contain embedded global navigation satellite systems (GNSSs),
inertial measurement units (IMUs), cameras, and other sensors which are capable of …