2 citations · 4 across the 4 of their papers we have counts for
4 papers
Real-time SLAM Pipeline in Dynamics Environment
Alex Fu, Lingjie Kong
Inspired by the recent success of application of dense data approach by using ORB-SLAM and RGB-D SLAM, we propose a better pipeline of real-time SLAM in dynamics environment. Diffe…
Double A3C: Deep Reinforcement Learning on OpenAI Gym Games
Yangxin Zhong, Jiajie He, Lingjie Kong
Reinforcement Learning (RL) is an area of machine learning figuring out how agents take actions in an unknown environment to maximize its rewards. Unlike classical Markov Decision…
DeepSim: A Reinforcement Learning Environment Build Toolkit for ROS and Gazebo
Woong Gyu La, Lingjie Kong, Sunil Muralidhara +1
We propose DeepSim, a reinforcement learning environment build toolkit for ROS and Gazebo. It allows machine learning or reinforcement learning researchers to access the robotics d…
Unified Distributed Environment
Woong Gyu La, Sunil Muralidhara, Lingjie Kong +1
We propose Unified Distributed Environment (UDE), an environment virtualization toolkit for reinforcement learning research. UDE is designed to integrate environments built on any…