Nowadays, robots are increasingly used in densely populated dynamic environments.
Robots not only need to complete the navigation tasks quickly, but also need to take into …

Real-time navigation in dense human environments is a challenging problem in robotics.
Most existing path planners fail to account for the dynamics of pedestrians because …

In this paper, we present a novel path planning algorithm to achieve fast path planning in
complex environments. Most existing path planning algorithms are difficult to quickly find a …

Generating short and safe paths for mobile robots operating in crowded spaces is a hard
task due to the high uncertainty of each person's future behaviour. Classical path planning …

Many path planning algorithms are based on sampling the state space. While this approach
is very simple, it can become costly when the obstacles are unknown, since samples hitting …

Autonomous pedestrian-aware navigation in shared human-robot environments is a
challenging problem. Here we consider a common situation in which a large crowd of …

Social robot navigation aims to generate human-friendly paths in human-robot interactive
environments. This paper focuses on maintaining humans' physical safety and mental …

Nowadays, one of the emergent challenges in mobile robotics consists of navigating safely
and efficiently in dynamic environments populated by people. This paper focuses on the …

The paper proposes a motion planning method using a deep reinforcement learning
algorithm, Asynchronous Advantage Actor-Critic (A3C). For mobile robot navigation tasks in …

Robot navigation in human crowds remains the challenge of understanding human
behaviors in different scenarios. We present an approach for interactive and human-friendly …