For autonomous driving, traversability analysis is one of the most basic and essential tasks.
In this paper, we propose a novel LiDAR‐based terrain modeling approach, which could …

Terrain traversability mapping plays an important role in autonomous exploration of
unmanned ground vehicles. In many cases, information from a single sensor such as LiDAR …

For autonomous driving on rural or dirt roads-neither urban nor off-road-a large terrain area
needs to be estimated at high spatial resolution. However, available computing time is very …

Terrain traversability analysis is a challenging problem for mobile robots to adapt to complex
environments, including the detection of cluttered obstacles, potholes, or even slopes. With …

In this paper, a novel and complete navigation system is proposed for mobile ground
vehicles in a park environment. LiDAR map representation and maintenance, dynamic …

Autonomous navigation (also known as self-driving) has rapidly advanced in the last decade
for on-road vehicles. In contrast, off-road vehicles still lag in autonomous navigation …

Estimating the traversability of rough terrain is a critical task for an outdoor mobile robot.
While classifying structured environment can be learned from large number of training data …

Safe and reliable autonomous navigation in unstructured environments remains a challenge
for field robots. In particular, operating on vegetated terrain is problematic, because simple …

State-of-the-art autonomous driving systems rely on high definition (HD) maps for
localization and navigation. However, building and maintaining HD maps is time-consuming …

Autonomous navigation in dense vegetation remains an open challenge and is an area of
major interest for the research community. In this paper we propose a novel traversability …