9 citations · 22 across the 8 of their papers we have counts for
4 papers · 1 filter
Crowd-Aware Robot Navigation for Pedestrians with Multiple Collision Avoidance Strategies via Map-based Deep Reinforcement Learning
Shunyi Yao1, Guangda Chen, Quecheng Qiu +3
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 so…
NEARL: Non-Explicit Action Reinforcement Learning for Robotic Control
Nan Lin, Yuxuan Li, Yujun Zhu +6
Traditionally, reinforcement learning methods predict the next action based on the current state. However, in many situations, directly applying actions to control systems or robot…
Semantic Task Planning for Service Robots in Open World
Guowei Cui, Wei Shuai, Xiaoping Chen
In this paper, we present a planning system based on semantic reasoning for a general-purpose service robot, which is aimed at behaving more intelligently in domains that contain i…
Robot Navigation with Map-Based Deep Reinforcement Learning
Guangda Chen, Lifan Pan, Yu'an Chen +5
This paper proposes an end-to-end deep reinforcement learning approach for mobile robot navigation with dynamic obstacles avoidance. Using experience collected in a simulation envi…