The majority of existing LiDAR odometry solutions are based on simple geometric features
such as points, lines or planes which cannot fully reflect the characteristics of surrounding …

Before their massive deployment, autonomous vehicles need to prove in complex scenarios
such that they can reach human driving proficiency while guaranteeing higher safety levels …

Occupancy Grids have been widely used for perception of the environment as they allow to
model the obstacles in the scene, as well as free and unknown space. Recently, there has …

Dynamic Occupancy Grids are a popular approach for the estimation of the environment in
autonomous driving applications. They offer several advantages, such as the capability to …

In the field of robotics and autonomous driving, dynamic occupancy grid maps (DOGMs) are
typically used to represent the position and velocity information of objects. Although three …

Autonomous vehicles today are highly dependent on high-definition maps of the area they
navigate in. This creates economic barriers in the way of the massive deployment of this …

Grid maps, especially occupancy grid maps, are ubiquitous in many mobile robot
applications. To simplify the process of learning the map, grid maps subdivide the world into …

Motion prediction is a key factor towards the full deployment of autonomous vehicles. It is
fundamental in order to ensure safety while navigating through highly interactive and …

Grid maps, especially occupancy grid maps, are ubiquitous in many mobile robot
applications. To simplify the process of learning the map, grid maps subdivide the world into …

Autonomous vehicles represent a transformative technological advancement with pro-found
implications for our future mobility and quality of life. These systems promise to sig-nificantly …