activity
20182022
most citedSimulation-based Lidar Super-resolution for Ground Vehicles

2 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

cs.RO2022

Virtual Maps for Autonomous Exploration of Cluttered Underwater Environments

Jinkun Wang, Fanfei Chen, Yewei Huang +3

We consider the problem of autonomous mobile robot exploration in an unknown environment, taking into account a robot's coverage rate, map uncertainty, and state estimation uncerta…

cs.RO2021

Zero-Shot Reinforcement Learning on Graphs for Autonomous Exploration Under Uncertainty

Fanfei Chen, Paul Szenher, Yewei Huang +4

This paper studies the problem of autonomous exploration under localization uncertainty for a mobile robot with 3D range sensing. We present a framework for self-learning a high-pe…

cs.RO20201 cited

Autonomous Exploration Under Uncertainty via Deep Reinforcement Learning on Graphs

Fanfei Chen, John D. Martin, Yewei Huang +2

We consider an autonomous exploration problem in which a range-sensing mobile robot is tasked with accurately mapping the landmarks in an a priori unknown environment efficiently i…

cs.RO20202 cited

Simulation-based Lidar Super-resolution for Ground Vehicles

Tixiao Shan, Jinkun Wang, Fanfei Chen +2

We propose a methodology for lidar super-resolution with ground vehicles driving on roadways, which relies completely on a driving simulator to enhance, via deep learning, the appa…

cs.LG2018

Sparse Gaussian Process Temporal Difference Learning for Marine Robot Navigation

John Martin, Jinkun Wang, Brendan Englot

We present a method for Temporal Difference (TD) learning that addresses several challenges faced by robots learning to navigate in a marine environment. For improved data efficien…