Applying the learning mechanism of natural living beings to endow intelligent robots with
humanoid perception and decision-making wisdom becomes an important force to promote …

Moving in complex environments is an essential capability of intelligent mobile robots.
Decades of research and engineering have been dedicated to developing sophisticated …

Research in autonomous driving has benefited from a number of visual datasets collected
from mobile platforms, leading to improved visual perception, greater scene understanding …

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 …

This letter presents a learning-based approach to consider the effect of unobservable world
states in kinodynamic motion planning in order to enable accurate high-speed off-road …

Existing autonomous robot navigation systems allow robots to move from one point to
another in a collision-free manner. However, when facing new environments, these systems …

Classical autonomous navigation systems can control robots in a collision-free manner,
oftentimes with verifiable safety and explainability. When facing new environments …

While classical approaches to autonomous robot navigation currently enable operation in
certain environments, they break down in tightly constrained spaces, eg, where the robot …

The process of designing costmaps for off-road driving tasks is often a challenging and
engineering-intensive task. Recent work in costmap design for off-road driving focuses on …

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 …