25 citations · 28 across the 14 of their papers we have counts for
14 papers
Learning Asynchronous Upper-body Task-space Trajectory Tracking Policy for Humanoid Robots
Yumeng Liu, Dongqi Wang, Jiyu Yu +3
High-level humanoid planners often output sparse task-space, low-rate trajectories, whereas whole-body controllers run at high frequency. This creates temporal asynchrony between t…
G2G: Exploiting Intra-Group Geometry for Inter-Group Pose Estimation
Yufei Wei, Shuhao Ye, Chenxiao Hu +5
Recovering the relative 6-DoF pose between two image groups underlies cross-sequence relocalization and multi-camera rig odometry. Each group carries known intra-group geometry fro…
Neural Ranging Inertial Odometry
Si Wang, Bingqi Shen, Fei Wang +3
Ultra-wideband (UWB) has shown promising potential in GPS-denied localization thanks to its lightweight and drift-free characteristics, while the accuracy is limited in real scenar…
A Whole-Body Motion Imitation Framework from Human Data for Full-Size Humanoid Robot
Zhenghan Chen, Haodong Zhang, Dongqi Wang +4
Motion imitation is a pivotal and effective approach for humanoid robots to achieve a more diverse range of complex and expressive movements, making their performances more human-l…
Natural Humanoid Robot Locomotion with Generative Motion Prior
Haodong Zhang, Liang Zhang, Zhenghan Chen +3
Natural and lifelike locomotion remains a fundamental challenge for humanoid robots to interact with human society. However, previous methods either neglect motion naturalness or r…
Compliance while resisting: a shear-thickening fluid controller for physical human-robot interaction
Lu Chen, Lipeng Chen, Xiangchi Chen +6
Physical human-robot interaction (pHRI) is widely needed in many fields, such as industrial manipulation, home services, and medical rehabilitation, and puts higher demands on the…
UniMM: A Unified Mixture Model Framework for Multi-Agent Simulation
Longzhong Lin, Xuewu Lin, Kechun Xu +4
Simulation plays a crucial role in assessing autonomous driving systems, where the generation of realistic multi-agent behaviors is a key aspect. In multi-agent simulation, the pri…
RING#: PR-by-PE Global Localization with Roto-translation Equivariant Gram Learning
Sha Lu, Xuecheng Xu, Yuxuan Wu +4
Global localization using onboard perception sensors, such as cameras and LiDARs, is crucial in autonomous driving and robotics applications when GPS signals are unreliable. Most a…
Pretraining-finetuning Framework for Efficient Co-design: A Case Study on Quadruped Robot Parkour
Ci Chen, Jiyu Yu, Haojian Lu +3
In nature, animals with exceptional locomotion abilities, such as cougars, often possess asymmetric fore and hind legs. This observation inspired us: could optimizing the leg lengt…
EDA: Evolving and Distinct Anchors for Multimodal Motion Prediction
Longzhong Lin, Xuewu Lin, Tianwei Lin +3
Motion prediction is a crucial task in autonomous driving, and one of its major challenges lands in the multimodality of future behaviors. Many successful works have utilized mixtu…
Semantics-aware Motion Retargeting with Vision-Language Models
Haodong Zhang, ZhiKe Chen, Haocheng Xu +6
Capturing and preserving motion semantics is essential to motion retargeting between animation characters. However, most of the previous works neglect the semantic information or r…
A Two-stage Based Social Preference Recognition in Multi-Agent Autonomous Driving System
Jintao Xue, Dongkun Zhang, Rong Xiong +2
Multi-Agent Reinforcement Learning (MARL) has become a promising solution for constructing a multi-agent autonomous driving system (MADS) in complex and dense scenarios. But most m…
Exploiting Point-Wise Attention in 6D Object Pose Estimation Based on Bidirectional Prediction
Yuhao Yang, Jun Wu, Yue Wang +2
Traditional geometric registration based estimation methods only exploit the CAD model implicitly, which leads to their dependence on observation quality and deficiency to occlusio…
Depth-Independent Depth Completion via Least Square Estimation
Xianze Fang, Yunkai Wang, Zexi Chen +2
The depth completion task aims to complete a per-pixel dense depth map from a sparse depth map. In this paper, we propose an efficient least square based depth-independent method t…