Automated driving systems (ADSs) promise a safe, comfortable and efficient driving
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …

Nowadays Convolutional Neural Networks (CNNs) are being employed in a wide range of
industrial technologies for a variety of sectors, such as medical, automotive, aviation …

A key aspect of robotics today is estimating the state (eg, position and orientation) of a robot,
based on noisy sensor data. This book targets students and practitioners of robotics by …

This article develops a Bayesian continuous 3D semantic occupancy map from noisy point
clouds by generalizing the Bayesian kernel inference model for building occupancy maps, a …

The fusion of Iterative Closest Point (ICP) registrations in existing state estimation
frameworks relies on an accurate estimation of their uncertainty. In this paper, we study the …

We present a novel method to fuse the power of deep networks with the computational
efficiency of geometric and probabilistic localization algorithms. In contrast to other methods …

Abstract Global Navigation Satellite Systems (GNSS) suffer from outliers and multipath
errors in urban environments. Some errors can be mitigated by adaptive sensor fusion …

In this letter, we consider improving the efficiency of information-based autonomous robot
exploration in unknown and complex environments. We first utilize Gaussian process (GP) …

We consider the problem of building accurate and descriptive 3D occupancy maps of an
environment from sparse and noisy range sensor data. We seek to accomplish this task by …

We present a method to incorporate global orientation information from the sun into a visual
odometry pipeline using only the existing image stream, where the sun is typically not …