Deep Imitation Learning for Autonomous Navigation in Dynamic Pedestrian Environments
Lei Qin Zefan Huang Chen Zhang Hongliang Guo Marcelo Ang Daniela Rus Lei Qin Zefan Huang Chen Zhang Hongliang Guo Marcelo Ang Daniela Rus
Navigation through dynamic pedestrian environments in a socially compliant manner is still a challenging task for autonomous vehicles. Classical methods usually lead to unnatural vehicle behaviours for pedestrian navigation due to the difficulty in modeling social conventions mathematically. This paper presents an end-to-end path planning system that achieves autonomous navigation in dynamic envir...