Despite decades of research, existing navigation systems still face real-world challenges
when deployed in the wild, eg, in cluttered home environments or in human-occupied public …

Most conventional wheeled robots can only move in flat environments and simply divide
their planar workspaces into free spaces and obstacles. Deeming obstacles as non …

Most autonomous navigation systems assume wheeled robots are rigid bodies and their 2D
planar workspaces can be divided into free spaces and obstacles. However, recent wheeled …

Traversability illustrates the difficulty of driving through a specific region and encompasses
the suitability of the terrain for traverse based on its physical properties, such as slope and …

Terrain awareness, ie, the ability to identify and distinguish different types of terrain, is a
critical ability that robots must have to succeed at autonomous off-road navigation. Current …

Self-supervised learning is a powerful approach for developing traversability models for off-
road navigation, but these models often struggle with inputs unseen during training. Existing …

Accurate control of robots at high speeds requires a control system that can take into
account the kinodynamic interactions of the robot with the environment. Prior works on …

Terrain awareness, ie, the ability to sufficiently represent key differences in terrain, is a
critical ability that robots must have in order to be able to succeed at autonomous off-road …

Self-driving vehicles and autonomous ground robots require a reliable and accurate method
to analyze the traversability of the surrounding environment for safe navigation. This paper …

Empowering robots to navigate in a socially compliant manner is essential for the
acceptance of robots moving in human-inhabited environments. Previously, roboticists have …