In this article, we propose a novel safety specification tool, called the distributionally robust
risk map (DR-risk map), for a mobile robot operating in a learning-enabled environment …

Mobile cable-driven parallel robot (MCDPR) is a variant of cable-driven parallel robots
(CDPRs) by mounting several mobile bases to replace the conventional fixed frame. The …

Currently, almost all robot state estimation and localization systems are based on the
Kalman filter (KF) and its derived methods, in particular the unscented Kalman filter (UKF) …

With the increasing utilization of sampling-based path planning methods in the field of
mobile robots, the RRT* algorithm faces challenges in complex indoor scenes, including …

The ability to avoid the moving obstacle is critical to cable-driven parallel robots (CDPRs)
operating in real-world environments. However, the moving obstacle raises extraordinary …

Safe trajectory planning in highly dynamic environments remains a substantial challenge.
Traditional risk-based trajectory planning algorithms solve planning problems in …

Safe autonomous navigation of robots in complex and cluttered environments is a crucial
task and is still an open challenge even in 2D environments. Being able to efficiently …

As advanced features integrate into vehicle, drivers may feel apprehensive to use them.
Providing users information using human-machine interfaces (HMIs) may ease fears; …

The current trend in electric autonomous vehicles design is based on pre-existing models of
cities which have been built for cars. The carbon footprint of cities cannot be reduced until …

Application of deep learning to geometric 3D data poses various challenges for researchers.
The complex nature of geometric 3D data allows to represent it in different forms: occupancy …