8 citations · 24 across the 15 of their papers we have counts for
9 papers · 1 filter
Combining Improvements for Exploiting Dependency Trees in Neural Semantic Parsing
Defeng Xie, Jianmin Ji, Jiafei Xu +1
The dependency tree of a natural language sentence can capture the interactions between semantics and words. However, it is unclear whether those methods which exploit such depende…
A Q-learning Control Method for a Soft Robotic Arm Utilizing Training Data from a Rough Simulator
Peijin Li, Gaotian Wang, Hao Jiang +4
It is challenging to control a soft robot, where reinforcement learning methods have been applied with promising results. However, due to the poor sample efficiency, reinforcement…
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…
DRQN-based 3D Obstacle Avoidance with a Limited Field of View
Yu'an Chen, Guangda Chen, Lifan Pan +4
In this paper, we propose a map-based end-to-end DRL approach for three-dimensional (3D) obstacle avoidance in a partially observed environment, which is applied to achieve autonom…
Reinforcement Learning for Robot Navigation with Adaptive Forward Simulation Time (AFST) in a Semi-Markov Model
Yu'an Chen, Ruosong Ye, Ziyang Tao +7
Deep reinforcement learning (DRL) algorithms have proven effective in robot navigation, especially in unknown environments, by directly mapping perception inputs into robot control…
Neighbor-Vote: Improving Monocular 3D Object Detection through Neighbor Distance Voting
Xiaomeng Chu, Jiajun Deng, Yao Li +4
As cameras are increasingly deployed in new application domains such as autonomous driving, performing 3D object detection on monocular images becomes an important task for visual…