224 citations · 712 across the 27 of their papers we have counts for
4 papers · 2 filters
Learning with Training Wheels: Speeding up Training with a Simple Controller for Deep Reinforcement Learning
Linhai Xie, Sen Wang, Stefano Rosa +2
Deep Reinforcement Learning (DRL) has been applied successfully to many robotic applications. However, the large number of trials needed for training is a key issue. Most of existi…
Learning with Stochastic Guidance for Navigation
Linhai Xie, Yishu Miao, Sen Wang +5
Due to the sparse rewards and high degree of environment variation, reinforcement learning approaches such as Deep Deterministic Policy Gradient (DDPG) are plagued by issues of hig…
OxIOD: The Dataset for Deep Inertial Odometry
Changhao Chen, Peijun Zhao, Chris Xiaoxuan Lu +3
Advances in micro-electro-mechanical (MEMS) techniques enable inertial measurements units (IMUs) to be small, cheap, energy efficient, and widely used in smartphones, robots, and d…
Defo-Net: Learning Body Deformation using Generative Adversarial Networks
Zhihua Wang, Stefano Rosa, Linhai Xie +4
Modelling the physical properties of everyday objects is a fundamental prerequisite for autonomous robots. We present a novel generative adversarial network (Defo-Net), able to pre…