activity
20182022
most citedLearning Hierarchical Control for Robust In-Hand Manipulation

1 citations · 2 across the 4 of their papers we have counts for

collaborators

7 papers

cs.GR2022

Online Motion Style Transfer for Interactive Character Control

Yingtian Tang, Jiangtao Liu, Cheng Zhou +1

Motion style transfer is highly desired for motion generation systems for gaming. Compared to its offline counterpart, the research on online motion style transfer under interactiv…

cs.RO20211 cited

Learning-based Fast Path Planning in Complex Environments

Jianbang Liu, Baopu Li, Tingguang Li +3

In this paper, we present a novel path planning algorithm to achieve fast path planning in complex environments. Most existing path planning algorithms are difficult to quickly fin…

cs.RO2021

Learning Robot Exploration Strategy with 4D Point-Clouds-like Information as Observations

Zhaoting Li, Tingguang Li, Jiankun Wang +1

Being able to explore unknown environments is a requirement for fully autonomous robots. Many learning-based methods have been proposed to learn an exploration strategy. In the fro…

cs.RO20191 cited

Learning Hierarchical Control for Robust In-Hand Manipulation

Tingguang Li, Krishnan Srinivasan, Max Qing-Hu Meng +2

Robotic in-hand manipulation has been a long-standing challenge due to the complexity of modelling hand and object in contact and of coordinating finger motion for complex manipula…

cs.RO2019

Learning to Solve a Rubik's Cube with a Dexterous Hand

Tingguang Li, Weitao Xi, Meng Fang +2

We present a learning-based approach to solving a Rubik's cube with a multi-fingered dexterous hand. Despite the promising performance of dexterous in-hand manipulation, solving co…

cs.RO2019

HouseExpo: A Large-scale 2D Indoor Layout Dataset for Learning-based Algorithms on Mobile Robots

Tingguang Li, Danny Ho, Chenming Li +3

As one of the most promising areas, mobile robots draw much attention these years. Current work in this field is often evaluated in a few manually designed scenarios, due to the la…