17 citations · 51 across the 29 of their papers we have counts for
10 papers · 1 filter
Robot Learning from Human Videos: A Survey
Junyi Ma, Erhang Zhang, Haoran Yang +4
A critical bottleneck hindering further advancement in embodied AI and robotics is the challenge of scaling robot data. To address this, the field of learning robot manipulation sk…
OGScene3D: Incremental Open-Vocabulary 3D Gaussian Scene Graph Mapping for Scene Understanding
Siting Zhu, Ziyun Lu, Guangming Wang +5
Open-vocabulary scene understanding is crucial for robotic applications, enabling robots to comprehend complex 3D environmental contexts and supporting various downstream tasks suc…
Towards the Vision-Sound-Language-Action Paradigm: The HEAR Framework for Sound-Centric Manipulation
Chang Nie, Tianchen Deng, Guangming Wang +2
While recent Vision-Language-Action (VLA) models have begun to incorporate audio, they typically treat sound as static pre-execution prompts or focus exclusively on human speech. T…
3D Gaussian Splatting in Robotics: A Survey
Siting Zhu, Guangming Wang, Xin Kong +2
Dense 3D representations of the environment have been a long-term goal in the robotics field. While previous Neural Radiance Fields (NeRF) representation have been prevalent for it…
RL-GSBridge: 3D Gaussian Splatting Based Real2Sim2Real Method for Robotic Manipulation Learning
Yuxuan Wu, Lei Pan, Wenhua Wu +4
Sim-to-Real refers to the process of transferring policies learned in simulation to the real world, which is crucial for achieving practical robotics applications. However, recent…
NeRFs in Robotics: A Survey
Guangming Wang, Lei Pan, Songyou Peng +7
Detailed and realistic 3D environment representations have been a long-standing goal in the fields of computer vision and robotics. The recent emergence of neural implicit represen…
LHMap-loc: Cross-Modal Monocular Localization Using LiDAR Point Cloud Heat Map
Xinrui Wu, Jianbo Xu, Puyuan Hu +2
Localization using a monocular camera in the pre-built LiDAR point cloud map has drawn increasing attention in the field of autonomous driving and mobile robotics. However, there a…
SemGauss-SLAM: Dense Semantic Gaussian Splatting SLAM
Siting Zhu, Renjie Qin, Guangming Wang +2
We propose SemGauss-SLAM, a dense semantic SLAM system utilizing 3D Gaussian representation, that enables accurate 3D semantic mapping, robust camera tracking, and high-quality ren…
SNI-SLAM: Semantic Neural Implicit SLAM
Siting Zhu, Guangming Wang, Hermann Blum +4
We propose SNI-SLAM, a semantic SLAM system utilizing neural implicit representation, that simultaneously performs accurate semantic mapping, high-quality surface reconstruction, a…
Learning of Long-Horizon Sparse-Reward Robotic Manipulator Tasks with Base Controllers
Guangming Wang, Minjian Xin, Wenhua Wu +2
Deep Reinforcement Learning (DRL) enables robots to perform some intelligent tasks end-to-end. However, there are still many challenges for long-horizon sparse-reward robotic manip…