136 citations · 327 across the 11 of their papers we have counts for
7 papers · 1 filter
milliEgo: Single-chip mmWave Radar Aided Egomotion Estimation via Deep Sensor Fusion
Chris Xiaoxuan Lu, Muhamad Risqi U. Saputra, Peijun Zhao +6
Robust and accurate trajectory estimation of mobile agents such as people and robots is a key requirement for providing spatial awareness for emerging capabilities such as augmente…
Deep Learning based Pedestrian Inertial Navigation: Methods, Dataset and On-Device Inference
Changhao Chen, Peijun Zhao, Chris Xiaoxuan Lu +3
Modern inertial measurements units (IMUs) are small, cheap, energy efficient, and widely employed in smart devices and mobile robots. Exploiting inertial data for accurate and reli…
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…