Background: The purpose of this study is to examine, using bibliometric methods, the work
done on behavior prediction of traffic actors for autonomous vehicles using various artificial …

As changes in external environments are inevitable, a lifelong mapping system is desirable
for autonomous robots that aim at long-term operation. Capturing external environment …

The use of autonomous vehicles on public roads and in industrial environments has been
growing in recent years and to achieve the higher level of autonomy, where no human …

Nowadays, deep neural networks (DNN) are ubiquitous. Many of our daily problems have
been solved or alleviated with the help of such models. It is important to note, though, that …

In this work, we present a visual global localization system based on Deep Neural Networks
(DNNs) for self-driving cars, called DeepVGL (Deep Visual Global Localization), which …

To improve dynamic tracking and pointing accuracy on unstable platforms, this paper
designs a parallel closed-loop control approach based on on-axis tracking theory. This …

We present a path planner for unstructured urban environments (PPUE) for self-driving cars.
PPUE receives initial and goal poses as input, as well as maps of the environment. It …

We propose a new approach for real time inference of occupancy maps for self-driving cars
using deep neural networks (DNN) named NeuralMapper. NeuralMapper receives LiDAR …

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