As mobile robots are increasingly introduced into our daily lives, it grows ever more
imperative that these robots navigate with and among people in a safe and socially …

Socially aware robot navigation is gaining popularity with the increase in delivery and
assistive robots. The research is further fueled by a need for socially aware navigation skills …

Human behavior prediction models enable robots to anticipate how humans may react to
their actions, and hence are instrumental to devising safe and proactive robot planning …

A major challenge to deploying robots widely is navigation in human-populated
environments, commonly referred to as social robot navigation. While the field of social …

Reinforcement learning continuously optimizes decision-making based on real-time
feedback reward signals through continuous interaction with the environment …

We present ProxEmo, a novel end-to-end emotion prediction algorithm for socially aware
robot navigation among pedestrians. Our approach predicts the perceived emotions of a …

We present a novel, real-time algorithm, EVA, for generating virtual agents with various
perceived emotions. Our approach is based on using Expressive Features of gaze and gait …

Moving in dynamic pedestrian environments is one of the important requirements for
autonomous mobile robots. We present a model-based reinforcement learning approach for …

传统的路径规划算法只能在障碍物不发生位置变化的环境中计算最优路径.
但是随着机器人在商场, 医院, 银行等动态环境下的普及, 传统的路径规划算法容易与动态障碍物 …

Developing autonomous vehicles capable of navigating safely and socially around
pedestrians is a major challenge in intelligent transportation. This challenge cannot be met …