1 citations · 1 across the 13 of their papers we have counts for
13 papers
CR-VLA-Force: Learning Control-aware Compliance VLA Model for Robust Contact-rich Robotic Manipulation
Zhaohong Mai, Chao Wang, Chao Zeng +4
Integrating visuomotor policies or Vision-Language-Action (VLA) models with force/torque (F/T) perception has demonstrated significant progress in imitation learning for robotic ma…
Revisiting Topological Graphs for Macro Action based Closed-loop Reinforcement Learning of Vision Language Navigation in Continuous Environment
Shuhao Ye, Sitong Mao, Yuxiang Cui +7
Vision-Language Navigation in Continuous Environments (VLN-CE) requires an agent to follow natural language instructions through unseen environments. Existing imitation learning (I…
EventVLA: Event-Driven Visual Evidence Memory for Long-Horizon Vision-Language-Action Policies
Ganlin Yang, Zhangzheng Tu, Yuqiang Yang +10
Memory remains a critical bottleneck for long-horizon robotic manipulation, as standard Vision-Language-Action (VLA) policies often fail when task-relevant cues become occluded or…
HyperSim: A Holistic Sim-To-Real Framework For Robust Robotic Manipulation
Junyi Dong, Haotian Luo, Ziwei Xu +11
Scaling data volume and diversity is critical for generalizing embodied intelligence. While synthetic data generation offers a scalable alternative to expensive physical data acqui…
ETP-R1: Evolving Topological Planning with Reinforcement Fine-tuning for Vision-Language Navigation in Continuous Environments
Shuhao Ye, Sitong Mao, Yuxiang Cui +6
Vision-Language Navigation in Continuous Environments (VLN-CE) requires an embodied agent to navigate towards target in continuous environments, following natural language instruct…
Spatial Reasoning with Vision-Language Models in Ego-Centric Multi-View Scenes
Mohsen Gholami, Ahmad Rezaei, Zhou Weimin +4
Understanding 3D spatial relationships remains a major limitation of current Vision-Language Models (VLMs). Prior work has addressed this issue by creating spatial question-answeri…
Discrete Diffusion VLA: Bringing Discrete Diffusion to Action Decoding in Vision-Language-Action Policies
Zhixuan Liang, Yizhuo Li, Tianshuo Yang +9
Vision-Language-Action (VLA) models adapt large vision-language backbones to map images and instructions into robot actions. However, prevailing VLAs either generate actions autore…
Dynamic Mixture of Progressive Parameter-Efficient Expert Library for Lifelong Robot Learning
Yuheng Lei, Sitong Mao, Shunbo Zhou +3
A generalist agent must continuously learn and adapt throughout its lifetime, achieving efficient forward transfer while minimizing catastrophic forgetting. Previous work within th…
PanopticSplatting: End-to-End Panoptic Gaussian Splatting
Yuxuan Xie, Xuan Yu, Changjian Jiang +5
Open-vocabulary panoptic reconstruction is a challenging task for simultaneous scene reconstruction and understanding. Recently, methods have been proposed for 3D scene understandi…
Scale Disparity of Instances in Interactive Point Cloud Segmentation
Chenrui Han, Xuan Yu, Yuxuan Xie +5
Interactive point cloud segmentation has become a pivotal task for understanding 3D scenes, enabling users to guide segmentation models with simple interactions such as clicks, the…
Let Occ Flow: Self-Supervised 3D Occupancy Flow Prediction
Yili Liu, Linzhan Mou, Xuan Yu +4
Accurate perception of the dynamic environment is a fundamental task for autonomous driving and robot systems. This paper introduces Let Occ Flow, the first self-supervised work fo…
PanopticRecon: Leverage Open-vocabulary Instance Segmentation for Zero-shot Panoptic Reconstruction
Xuan Yu, Yili Liu, Chenrui Han +5
Panoptic reconstruction is a challenging task in 3D scene understanding. However, most existing methods heavily rely on pre-trained semantic segmentation models and known 3D object…
SCALE: Self-Correcting Visual Navigation for Mobile Robots via Anti-Novelty Estimation
Chang Chen, Yuecheng Liu, Yuzheng Zhuang +3
Although visual navigation has been extensively studied using deep reinforcement learning, online learning for real-world robots remains a challenging task. Recent work directly le…