Navigating efficiently and safely through human crowds is essential for mobile robots in
diverse applications such as delivery services, home assistance, healthcare, and …

The growing development of autonomous systems is driving the application of mobile robots
in crowded environments. These scenarios often require robots to satisfy multiple conflicting …

Ensuring safe and efficient navigation in crowded environments is a critical goal for assistive
robots. Recent studies have emphasized the potential of deep reinforcement learning …

The evolution of learning techniques has led robotics to have a considerable influence in
industrial and household applications. With the progress in technology revolution, the …

Current state-of-the-art crowd navigation approaches are mainly deep reinforcement
learning (DRL)-based. However, DRL-based methods suffer from the issues of …

Achieving safe and effective navigation in crowds is a crucial yet challenging problem.
Recent work has mainly encoded the pedestrian-robot state pairs, which cannot fully capture …

It is challenging for a mobile robot to navigate through human crowds. Existing approaches
usually assume that pedestrians follow a predefined collision avoidance strategy, like social …

For the scene of dense crowd flow in limited space, it is very important and challenging for
the robot to walk through the dense crowd without collision and move to the destination …

Real-world robot applications usually require navigating agents to face multiple
destinations. Besides, the real-world crowded environments usually contain dynamic and …

Navigating in crowd environments is challenging for mobile robots because not only the
safety but also the comfort of surrounding pedestrians must be considered. In this work, a …