3 citations · 4 across the 37 of their papers we have counts for
38 papers
Refine Actions If Needed: Adaptive Action Chunk Refinement for Robot Manipulation
Hanlin Liu, Zichen Zhou, Jiacheng Zhang +6
Computationally lightweight manipulation policies predict executable actions with low inference latency, but prediction errors can limit task success. Iterative generative policies…
OmniNav: Robust Long-Horizon Target Navigation in Dynamic Environments
Yujie Tang, Meiling Wang, Jinhao Jiang +4
Long-horizon target navigation requires a robot to sustain task execution across evolving observations, decisions, and physical interactions. This requires three coupled capabiliti…
PhysReal: Learning Real-World Deformable Object Physics via Hybrid Constitutive Modeling
Yinan Deng, Jianqiao Song, Yisi Zhang +3
Learning physically plausible dynamics from visual observations is essential for interactive world models and embodied agents. However, modeling real-world deformable objects remai…
HOST:Robots Acquire Manipulation Skills in Seconds from a Single Human Video
Guangyan Chen, Meiling Wang, Te Cui +9
The ability to acquire skills rapidly and effortlessly while retaining those already mastered is essential for robots. However, current methods still rely on a cumbersome training-…
NeSy-CSA: A Neuro-Symbolic Framework for Open-Ended Critical Scenario Attribution
Qitong Chu, Xunjie He, Chen Deng +2
Understanding why discovered scenarios become critical in scenario-based testing is essential for effectively leveraging them in decision-making systems. Reasoning about such criti…
PDS Joint: A Parametric Double-Spiral Joint Tailored for Dexterous Hands
Haoyang Li, Yibo Wen, Yixiang Fan +2
Compliant joints can embed safety and adaptability into dexterous hands, but achieving large-stroke anthropomorphic motion while maintaining joint-specific, directiondependent stif…
PaMoSplat: Part-Aware Motion-Guided Gaussian Splatting for Dynamic Scene Reconstruction
Yinan Deng, Jianyu Dou, Jiahui Wang +3
Dynamic scene reconstruction represents a fundamental yet demanding challenge in computer vision and robotics. While recent progress in 3DGS-based methods has advanced dynamic scen…
FilterGS: Traversal-Free Parallel Filtering and Adaptive Shrinking for Large-Scale LoD 3D Gaussian Splatting
Yixian Wang, Haolin Yu, Jiadong Tang +4
3D Gaussian Splatting has revolutionized neural rendering with real-time performance. However, scaling this approach to large scenes using Level-of-Detail methods faces critical ch…
See Once, Then Act: Vision-Language-Action Model with Task Learning from One-Shot Video Demonstrations
Guangyan Chen, Meiling Wang, Qi Shao +10
Developing robust and general-purpose manipulation policies represents a fundamental objective in robotics research. While Vision-Language-Action (VLA) models have demonstrated pro…
GLUE: Global-Local Unified Encoding for Imitation Learning via Key-Patch Tracking
Ye Chen, Zichen Zhou, Jianyu Dou +3
In recent years, visual representation learning has gained widespread attention in robotic imitation learning. However, in complex Out-of-Distribution(OOD) settings characterized b…
OmniMap: A General Mapping Framework Integrating Optics, Geometry, and Semantics
Yinan Deng, Yufeng Yue, Jianyu Dou +5
Robotic systems demand accurate and comprehensive 3D environment perception, requiring simultaneous capture of photo-realistic appearance (optical), precise layout shape (geometric…
OpenMulti: Open-Vocabulary Instance-Level Multi-Agent Distributed Implicit Mapping
Jianyu Dou, Yinan Deng, Jiahui Wang +3
Multi-agent distributed collaborative mapping provides comprehensive and efficient representations for robots. However, existing approaches lack instance-level awareness and semant…
OpenGS-Fusion: Open-Vocabulary Dense Mapping with Hybrid 3D Gaussian Splatting for Refined Object-Level Understanding
Dianyi Yang, Xihan Wang, Yu Gao +4
Recent advancements in 3D scene understanding have made significant strides in enabling interaction with scenes using open-vocabulary queries, particularly for VR/AR and robotic ap…
FMimic: Foundation Models are Fine-grained Action Learners from Human Videos
Guangyan Chen, Meiling Wang, Te Cui +8
Visual imitation learning (VIL) provides an efficient and intuitive strategy for robotic systems to acquire novel skills. Recent advancements in foundation models, particularly Vis…
STEP Planner: Constructing cross-hierarchical subgoal tree as an embodied long-horizon task planner
Tianxing Zhou, Zhirui Wang, Haojia Ao +5
The ability to perform reliable long-horizon task planning is crucial for deploying robots in real-world environments. However, directly employing Large Language Models (LLMs) as a…
TASeg: Text-aware RGB-T Semantic Segmentation based on Fine-tuning Vision Foundation Models
Meng Yu, Te Cui, Qitong Chu +3
Reliable semantic segmentation of open environments is essential for intelligent systems, yet significant problems remain: 1) Existing RGB-T semantic segmentation models mainly rel…
MCOO-SLAM: A Multi-Camera Omnidirectional Object SLAM System
Miaoxin Pan, Jinnan Li, Yaowen Zhang +2
Object-level SLAM offers structured and semantically meaningful environment representations, making it more interpretable and suitable for high-level robotic tasks. However, most e…
DINO-CoDT: Multi-class Collaborative Detection and Tracking with Vision Foundation Models
Xunjie He, Christina Dao Wen Lee, Meiling Wang +4
Collaborative perception plays a crucial role in enhancing environmental understanding by expanding the perceptual range and improving robustness against sensor failures, which pri…
DroneSplat: 3D Gaussian Splatting for Robust 3D Reconstruction from In-the-Wild Drone Imagery
Jiadong Tang, Yu Gao, Dianyi Yang +3
Drones have become essential tools for reconstructing wild scenes due to their outstanding maneuverability. Recent advances in radiance field methods have achieved remarkable rende…
GaussianGraph: 3D Gaussian-based Scene Graph Generation for Open-world Scene Understanding
Xihan Wang, Dianyi Yang, Yu Gao +3
Recent advancements in 3D Gaussian Splatting(3DGS) have significantly improved semantic scene understanding, enabling natural language queries to localize objects within a scene. H…
OpenGS-SLAM: Open-Set Dense Semantic SLAM with 3D Gaussian Splatting for Object-Level Scene Understanding
Dianyi Yang, Yu Gao, Xihan Wang +3
Recent advancements in 3D Gaussian Splatting have significantly improved the efficiency and quality of dense semantic SLAM. However, previous methods are generally constrained by l…
ChatStitch: Visualizing Through Structures via Surround-View Unsupervised Deep Image Stitching with Collaborative LLM-Agents
Hao Liang, Zhipeng Dong, Kaixin Chen +4
Surround-view perception has garnered significant attention for its ability to enhance the perception capabilities of autonomous driving vehicles through the exchange of informatio…
OpenVox: Real-time Instance-level Open-vocabulary Probabilistic Voxel Representation
Yinan Deng, Bicheng Yao, Yihang Tang +2
In recent years, vision-language models (VLMs) have advanced open-vocabulary mapping, enabling mobile robots to simultaneously achieve environmental reconstruction and high-level s…
OpenIN: Open-Vocabulary Instance-Oriented Navigation in Dynamic Domestic Environments
Yujie Tang, Meiling Wang, Yinan Deng +3
In daily domestic settings, frequently used objects like cups often have unfixed positions and multiple instances within the same category, and their carriers frequently change as…