activity
20202023
most citedRadar SLAM: A Robust SLAM System for All Weather Conditions

19 citations · 37 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2023

Cross-Dimensional Refined Learning for Real-Time 3D Visual Perception from Monocular Video

Ziyang Hong, C. Patrick Yue

We present a novel real-time capable learning method that jointly perceives a 3D scene's geometry structure and semantic labels. Recent approaches to real-time 3D scene reconstruct…

cs.RO2022

CURL: Continuous, Ultra-compact Representation for LiDAR

Kaicheng Zhang, Ziyang Hong, Shida Xu +1

Increasing the density of the 3D LiDAR point cloud is appealing for many applications in robotics. However, high-density LiDAR sensors are usually costly and still limited to a lev…

cs.RO2021★ 19 cited

Radar SLAM: A Robust SLAM System for All Weather Conditions

Ziyang Hong, Yvan Petillot, Andrew Wallace +1

A Simultaneous Localization and Mapping (SLAM) system must be robust to support long-term mobile vehicle and robot applications. However, camera and LiDAR based SLAM systems can be…

cs.LG2021

Efficient Training Convolutional Neural Networks on Edge Devices with Gradient-pruned Sign-symmetric Feedback Alignment

Ziyang Hong, C. Patrick Yue

With the prosperity of mobile devices, the distributed learning approach enabling model training with decentralized data has attracted wide research. However, the lack of training…

cs.RO2020★ 1 cited

Multi-Task Reinforcement Learning based Mobile Manipulation Control for Dynamic Object Tracking and Grasping

Cong Wang, Qifeng Zhang, Qiyan Tian +6

Agile control of mobile manipulator is challenging because of the high complexity coupled by the robotic system and the unstructured working environment. Tracking and grasping a dy…

cs.RO2020★ 17 cited

RadarSLAM: Radar based Large-Scale SLAM in All Weathers

Ziyang Hong, Yvan Petillot, Sen Wang

Numerous Simultaneous Localization and Mapping (SLAM) algorithms have been presented in last decade using different sensor modalities. However, robust SLAM in extreme weather condi…