Learning Crowd-Aware Robot Navigation from Challenging Environments via Distributed Deep Reinforcement Learning
Sango Matsuzaki,Yuji Hasegawa,Sango Matsuzaki,Yuji Hasegawa
This paper presents a deep reinforcement learning (DRL) sframework for safe and efficient navigation in crowded environments. Here, the robot learns cooperative behavior using a new reward function that penalizes robot actions interfering with the pedestrian's movement. Also, we propose a simulated pedestrian policy reflecting data from actual pedestrian movements. Furthermore, we introduce a coll...
