Robot navigation in crowded public spaces is a complex task that requires addressing a
variety of engineering and human factors challenges. These challenges have motivated a …

A fundamental task in robotics is to plan collision‐free motions among a set of obstacles.
Recently, learning‐based motion‐planning methods have shown significant advantages in …

The exponentially increasing advances in robotics and machine learning are facilitating the
transition of robots from being confined to controlled industrial spaces to performing novel …

With the service robots are well used in more and more indoor environments, autonomous
navigation in such a human environment has been explored in recent decades. Different …

This paper addresses the problems related to the mapless navigation control of wheeled
mobile robots based on deep learning technology. The traditional navigation control …

This paper presents a novel knowledge-informed graph neural planner (KG-Planner) to
address the challenge of efficiently planning collision-free motions for robots in high …

Mobile robots are increasingly populating homes, hospitals, shopping malls, factory floors,
and other human environments. Human society has social norms that people mutually …

Machine learning (ML) has significantly enhanced the abilities of robots, enabling them to
perform a wide range of tasks in human environments and adapt to our uncertain real world …

Robots increasingly interact with humans through touch, where people are touching or
being touched by robots. Yet, little is known about how such interactions shape a user's …

The field of Unmanned Aerial Vehicles (UAVs) has reached a high level of maturity in the
last few years. Hence, bringing such platforms from closed labs, to day-to-day interactions …