18 citations · 31 across the 29 of their papers we have counts for
31 papers
LoopWAM: Closed-Loop Generalist Policy Improvement from Deployment Rollouts
Wenxuan Guo, Yingping Liang, Zhaoguo Wang +11
Scaling expert demonstrations alone does not enable generalist robot policies to improve from deployment. Real-world rollouts contain successes, suboptimal behavior, and failures:…
SkillMemo: Expert-guided Skill Memory Framework for Compositional Embodied Manipulation
Changyuan Wang, Chubin Zhang, Zhenyu Wu +8
Embodied visuomotor models, including Diffusion Policy (DP) and Vision-Language-Action (VLA) models, have demonstrated promising performance on robotic manipulation benchmarks. How…
GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch
GigaWorld Team, Angen Ye, Angyuan Ma +26
World Action Models (WAMs) improve robot policy learning by jointly modeling actions and future visual observations, using future scene evolution as dense supervision for physicall…
R2RDreamer: 3D-aware Data Augmentation for Spatially-generalized 2D Manipulation Policies
Xiuwei Xu, Haowen Sun, Angyuan Ma +7
Spatial generalization is critical for imitation-learned manipulation policies, but achieving it typically requires scaling demonstrations across diverse object poses, robot config…
iMaC: Translating Actions into Motion and Contact Images for Embodied World Models
Zhenyu Wu, Xiuwei Xu, Yukun Zhou +8
Embodied world models have emerged as a pivotal paradigm for visual robotic decision-making and interactive environment simulation. However, conventional embodied frameworks rely o…
AwareVLN: Reasoning with Self-awareness for Vision-Language Navigation
Wenxuan Guo, Xiuwei Xu, Yichen Liu +7
Vision-and-Language Navigation (VLN) requires an agent to ground language instructions to its own movement within a visual environment. While state-of-the-art methods leverage the…
ShapeGen: Robotic Data Generation for Category-Level Manipulation
Yirui Wang, Xiuwei Xu, Angyuan Ma +3
Manipulation policies deployed in uncontrolled real-world scenarios are faced with great in-category geometric diversity of everyday objects. In order to function robustly under su…
F2F-AP: Flow-to-Future Asynchronous Policy for Real-time Dynamic Manipulation
Haoyu Wei, Xiuwei Xu, Ziyang Cheng +5
Asynchronous inference has emerged as a prevalent paradigm in robotic manipulation, achieving significant progress in ensuring trajectory smoothness and efficiency. However, a syst…
CMP: Robust Whole-Body Tracking for Loco-Manipulation via Competence Manifold Projection
Ziyang Cheng, Haoyu Wei, Hang Yin +4
While decoupled control schemes for legged mobile manipulators have shown robustness, learning holistic whole-body control policies for tracking global end-effector poses remains f…
iGaussian: Real-Time Camera Pose Estimation via Feed-Forward 3D Gaussian Splatting Inversion
Hao Wang, Linqing Zhao, Xiuwei Xu +2
Recent trends in SLAM and visual navigation have embraced 3D Gaussians as the preferred scene representation, highlighting the importance of estimating camera poses from a single i…
R2RGEN: Real-to-Real 3D Data Generation for Spatially Generalized Manipulation
Xiuwei Xu, Angyuan Ma, Hankun Li +4
Towards the aim of generalized robotic manipulation, spatial generalization is the most fundamental capability that requires the policy to work robustly under different spatial dis…
GC-VLN: Instruction as Graph Constraints for Training-free Vision-and-Language Navigation
Hang Yin, Haoyu Wei, Xiuwei Xu +3
In this paper, we propose a training-free framework for vision-and-language navigation (VLN). Existing zero-shot VLN methods are mainly designed for discrete environments or involv…
MoTo: A Zero-shot Plug-in Interaction-aware Navigation for General Mobile Manipulation
Zhenyu Wu, Angyuan Ma, Xiuwei Xu +5
Mobile manipulation stands as a core challenge in robotics, enabling robots to assist humans across varied tasks and dynamic daily environments. Conventional mobile manipulation ap…
Pseudo Depth Meets Gaussian: A Feed-forward RGB SLAM Baseline
Linqing Zhao, Xiuwei Xu, Yirui Wang +5
Incrementally recovering real-sized 3D geometry from a pose-free RGB stream is a challenging task in 3D reconstruction, requiring minimal assumptions on input data. Existing method…
IGL-Nav: Incremental 3D Gaussian Localization for Image-goal Navigation
Wenxuan Guo, Xiuwei Xu, Hang Yin +4
Visual navigation with an image as goal is a fundamental and challenging problem. Conventional methods either rely on end-to-end RL learning or modular-based policy with topologica…
EfficientLLaVA:Generalizable Auto-Pruning for Large Vision-language Models
Yinan Liang, Ziwei Wang, Xiuwei Xu +2
While multimodal large language models demonstrate strong performance in complex reasoning tasks, they pose significant challenges related to model complexity during deployment, es…
UniGoal: Towards Universal Zero-shot Goal-oriented Navigation
Hang Yin, Xiuwei Xu, Lingqing Zhao +3
In this paper, we propose a general framework for universal zero-shot goal-oriented navigation. Existing zero-shot methods build inference framework upon large language models (LLM…
MoManipVLA: Transferring Vision-language-action Models for General Mobile Manipulation
Zhenyu Wu, Yuheng Zhou, Xiuwei Xu +2
Mobile manipulation is the fundamental challenge for robotics to assist humans with diverse tasks and environments in everyday life. However, conventional mobile manipulation appro…
TSP3D: Text-guided Sparse Voxel Pruning for Efficient 3D Visual Grounding
Wenxuan Guo, Xiuwei Xu, Ziwei Wang +3
In this paper, we propose an efficient multi-level convolution architecture for 3D visual grounding. Conventional methods are difficult to meet the requirements of real-time infere…
SG-Nav: Online 3D Scene Graph Prompting for LLM-based Zero-shot Object Navigation
Hang Yin, Xiuwei Xu, Zhenyu Wu +2
In this paper, we propose a new framework for zero-shot object navigation. Existing zero-shot object navigation methods prompt LLM with the text of spatially closed objects, which…
Q-VLM: Post-training Quantization for Large Vision-Language Models
Changyuan Wang, Ziwei Wang, Xiuwei Xu +3
In this paper, we propose a post-training quantization framework of large vision-language models (LVLMs) for efficient multi-modal inference. Conventional quantization methods sequ…
EmbodiedSAM: Online Segment Any 3D Thing in Real Time
Xiuwei Xu, Huangxing Chen, Linqing Zhao +3
Embodied tasks require the agent to fully understand 3D scenes simultaneously with its exploration, so an online, real-time, fine-grained and highly-generalized 3D perception model…
Embodied Instruction Following in Unknown Environments
Zhenyu Wu, Ziwei Wang, Xiuwei Xu +5
Enabling embodied agents to complete complex human instructions from natural language is crucial to autonomous systems in household services. Conventional methods can only accompli…
Memory-based Adapters for Online 3D Scene Perception
Xiuwei Xu, Chong Xia, Ziwei Wang +4
In this paper, we propose a new framework for online 3D scene perception. Conventional 3D scene perception methods are offline, i.e., take an already reconstructed 3D scene geometr…